U.S. patent application number 13/070357 was filed with the patent office on 2011-07-14 for patient entry recording in an epilepsy monitoring system.
Invention is credited to John F. Harris, Kent W. Leyde.
Application Number | 20110172554 13/070357 |
Document ID | / |
Family ID | 39495963 |
Filed Date | 2011-07-14 |
United States Patent
Application |
20110172554 |
Kind Code |
A1 |
Leyde; Kent W. ; et
al. |
July 14, 2011 |
Patient Entry Recording in an Epilepsy Monitoring System
Abstract
Systems and methods for monitoring a patient are provided. The
system includes: an implantable sensor adapted to collect
neurological signals; an implantable assembly configured to sample
the neurological signals collected by the sensor; and a
rechargeable external assembly configured to wirelessly receive the
sampled neurological signals from the implantable assembly, said
external assembly being further configured to record a patient
entry in response to receiving an input from the patient. The
method includes: collecting neurological signals with a sensor
implanted in the patient; sampling the neurological signals
collected by the sensor with an implantable assembly implanted in
the patient; and transmitting the sampled neurological signals from
the implantable assembly to a rechargeable external assembly
external to the patient; and recording a patient entry in response
to receiving an input from the patient.
Inventors: |
Leyde; Kent W.; (Sammamish,
WA) ; Harris; John F.; (Bellevue, WA) |
Family ID: |
39495963 |
Appl. No.: |
13/070357 |
Filed: |
March 23, 2011 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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12020507 |
Jan 25, 2008 |
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13070357 |
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60897551 |
Jan 25, 2007 |
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Current U.S.
Class: |
600/544 |
Current CPC
Class: |
A61N 1/37247 20130101;
A61B 5/0006 20130101; A61N 1/37258 20130101; A61B 2560/0271
20130101; A61M 5/14276 20130101; G16H 40/67 20180101; A61N 1/37282
20130101; A61B 5/4094 20130101; A61B 5/0031 20130101; A61N 1/36082
20130101; A61B 5/369 20210101 |
Class at
Publication: |
600/544 |
International
Class: |
A61B 5/048 20060101
A61B005/048 |
Claims
1. A system for monitoring a patient, the system comprising: an
implantable sensor adapted to collect neurological signals; an
implantable assembly configured to sample the neurological signals
collected by the sensor; and a rechargeable external assembly
configured to wirelessly receive the sampled neurological signals
from the implantable assembly, said external assembly being further
configured to record a patient entry in response to receiving an
input from the patient.
2. The system of claim 1, wherein the external assembly is
configured to time stamp the patient entry by recording a time that
the patient entry was recorded.
3. The system of claim 1, wherein the patient entry comprises an
occurrence of a seizure.
4. The system of claim 1, wherein the patient entry comprises a
sleep state.
5. The system of claim 4, wherein the sleep state comprises the
patient going to sleep.
6. The system of claim 4, wherein the sleep state comprises the
patient waking up.
7. The system of claim 1, wherein the external assembly is
configured to record the patient entry by recording audio in
response to receiving the input from the patient.
8. The system of claim 1, wherein the patient entry comprises
intake of a medication.
9. The system of claim 1, wherein the implantable assembly is
configured to substantially continuously sample the neurological
signal and to transmit data representing the continuously sampled
neurological signal to the external assembly.
10. The system of claim 1, wherein the implantable sensor is
adapted to collect neurological signals from inside the patient's
skull.
11. The system of claim 1, wherein the implantable sensor is
adapted to collect neurological signals from a location between the
patient's skull and at least a layer of the patient's scalp.
12. The system of claim 1, wherein the implantable assembly
comprises a memory adapted to store the sampled neurological
signals.
13. The system of claim 12, wherein the memory is adapted to store
at least one day of sampled neurological signals.
14. The system of claim 12, wherein the memory is adapted to store
at least one week of sampled neurological signals.
15. The system of claim 12, wherein the memory is adapted to store
at least one month of sampled neurological signals.
16. The system of claim 1, wherein the external assembly comprises
a memory adapted to store the sampled neurological signals received
from the implantable assembly.
17. The system of claim 16, wherein the memory is adapted to store
at least one day of sampled neurological signals.
18. The system of claim 16, wherein the memory is adapted to store
at least one week of sampled neurological signals.
19. The system of claim 16, wherein the memory is adapted to store
at least one month of sampled neurological signals.
20. The system of claim 1, wherein at least one of the implantable
assembly and the external assembly is configured to analyze the
sampled neurological signals.
21. The system of claim 1, wherein at least one of the implantable
assembly and the external assembly is configured to analyze the
sampled neurological signals to determine when the patient is in an
ictal state.
22. The system of claim 1, wherein at least one of the implantable
assembly and the external assembly is configured to analyze the
sampled neurological signal to detect an electrographic seizure
onset.
23. A method of monitoring a patient, comprising: collecting
neurological signals with a sensor implanted in the patient;
sampling the neurological signals collected by the sensor with an
implantable assembly implanted in the patient; transmitting the
sampled neurological signals from the implantable assembly to a
rechargeable external assembly external to the patient; and
recording a patient entry in response to receiving an input from
the patient.
24. The method of claim 23, wherein said recording audio using the
external assembly comprises: receiving user input on the external
assembly; and in response to said user input, initiating an audio
recording using the external assembly.
25. The method of claim 23, wherein said recording the patient
entry using the external assembly comprises recording a time that
the patient entry was recorded.
26. The method of claim 23, wherein the patient entry comprises a
sleep state.
27. The method of claim 26, wherein the sleep state comprises the
patient going to sleep.
28. The method of claim 27, wherein the sleep state comprises the
patient waking up.
29. The method of claim 23, said recording the patient entry using
the external assembly comprises recording audio in response to
receiving the input from the patient.
30. The method of claim 23, wherein the patient entry comprises
intake of a medication.
31. The method of claim 23, wherein the patient entry comprises an
occurrence of a seizure.
32. The method of claim 31, further comprising comparing a number
of seizures recorded by the patient to a number of seizures
detected in the neurological signals.
33. The method of claim 23, wherein said sampling the neurological
signals with the implantable assembly comprises substantially
continuously sampling the neurological signals.
34. The method of claim 23, wherein said collecting neurological
signals comprises collecting neurological signals from inside the
patient's skull.
35. The method of claim 23, wherein said collecting neurological
signals comprises collecting neurological signals from a location
between the patient's skull and at least one layer of the patient's
scalp.
36. The method of claim 23, further comprising storing at least one
day of sampled neurological signals in a memory in the implantable
assembly.
37. The method of claim 23, further comprising storing at least one
week of sampled neurological signals in a memory in the implantable
assembly.
38. The method of claim 23, further comprising storing at least one
month of sampled neurological signals in a memory in the
implantable assembly.
39. The method of claim 23, further comprising storing at least one
day of sampled neurological signals in a memory in the external
assembly.
40. The method of claim 23, further comprising storing at least one
week of sampled neurological signals in a memory in the external
assembly.
41. The method of claim 23, further comprising storing at least one
month of sampled neurological signals in a memory in the external
assembly.
42. The method of claim 23, further comprising analyzing the
sampled neurological signals using the implantable assembly or the
external assembly.
43. The method of claim 42, wherein said analyzing comprises
analyzing the sampled neurological signals to determine when the
patient is in an ictal state.
44. The method of claim 42, wherein said analyzing comprises
analyzing the sampled neurological signal to detect an
electrographic seizure onset.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] The present application is a continuation of pending U.S.
patent application Ser. No. 12/020,507, filed Jan. 25, 2008, which
claims benefit of U.S. Provisional Patent Application No.
60/897,551, filed Jan. 25, 2007, the disclosures of which are
incorporated by reference herein in their entirety.
BACKGROUND OF THE INVENTION
[0002] The present invention relates generally to systems and
methods for sampling and processing one or more physiological
signals from a subject. More specifically, the present invention
relates to monitoring of one or more neurological signals from a
subject to determine a subject's susceptibility to a neurological
event, communicating the subject's susceptibility to the subject,
reducing a severity of seizures and/or preventing seizures. The
invention also relates to continuously storing neurological signals
from a subject to train algorithms to determine a subject's
susceptibility for having a seizure.
[0003] Epilepsy is a neurological disorder of the brain
characterized by chronic, recurring seizures. Seizures are a result
of uncontrolled discharges of electrical activity in the brain. A
seizure typically manifests itself as sudden, involuntary,
disruptive, and often destructive sensory, motor, and cognitive
phenomena. Seizures are frequently associated with physical harm to
the body (e.g., tongue biting, limb breakage, and burns), a
complete loss of consciousness, and incontinence. A typical
seizure, for example, might begin as spontaneous shaking of an arm
or leg and progress over seconds or minutes to rhythmic movement of
the entire body, loss of attention, loss of consciousness, and
voiding of urine or stool.
[0004] A single seizure most often does not cause significant
morbidity or mortality, but severe or recurring seizures (epilepsy)
results in major medical, social, and economic consequences.
Epilepsy is most often diagnosed in children and young adults,
making the long-term medical and societal burden severe for this
population of subjects. People with uncontrolled epilepsy are often
significantly limited in their ability to work in many industries
and usually cannot legally drive an automobile. An uncommon, but
potentially lethal form of seizure is called status epilepticus, in
which a seizure continues for more than 30 minutes. This continuous
seizure activity may lead to permanent brain damage, and can be
lethal if untreated.
[0005] While the exact cause of epilepsy is often uncertain,
epilepsy can result from head trauma (such as from a car accident
or a fall), infection (such as meningitis), stroke, or from
neoplastic, vascular or developmental abnormalities of the brain.
Approximately 70% of epileptic subjects, especially most forms that
are resistant to treatment (i.e., refractory), are idiopathic or of
unknown causes, and is generally presumed to be an inherited
genetic disorder.
[0006] Demographic studies have estimated the prevalence of
epilepsy at approximately 1% of the population, or approximately
2.5 million individuals in the United States alone. In order to
assess possible causes and to guide treatment, epileptologists
(both neurologists and neurosurgeons) typically evaluate subjects
with seizures with brain wave electrical analysis and imaging
studies, such as magnetic resonance imaging (MRI).
[0007] While there is no known cure for epilepsy, chronic usage of
anticonvulsant and antiepileptic medications can control seizures
in most people. For most cases of epilepsy, the disease is chronic
and requires chronic medications for treatment. The anticonvulsant
and antiepileptic medications do not actually correct the
underlying conditions that cause seizures. Instead, the
anticonvulsant and antiepileptic medications manage the subject's
epilepsy by reducing the frequency of seizures. There are a variety
of classes of antiepileptic drugs (AEDs), each acting by a distinct
mechanism or set of mechanisms.
[0008] AEDs generally suppress neural activity by a variety of
mechanisms, including altering the activity of cell membrane ion
channels and the susceptibility of action potentials or bursts of
action potentials to be generated. These desired therapeutic
effects are often accompanied by the undesired side effect of
sedation, nausea, dizziness, etc. Some of the fast acting AEDs,
such as benzodiazepine, are also primarily used as sedatives. Other
medications have significant non-neurological side effects, such as
gingival hyperplasia, a cosmetically undesirable overgrowth of the
gums, and/or a thickening of the skull, as occurs with phenyloin.
Furthermore, some AED are inappropriate for women of child bearing
age due to the potential for causing severe birth defects.
[0009] An estimated 70% of subjects will respond favorably to their
first AED monotherapy and no further medications will be required.
However, for the remaining 30% of the subjects, their first AED
will fail to fully control their seizures and they will be
prescribed a second AED--often in addition to the first--even if
the first AED does not stop or change a pattern or frequency of the
subject's seizures. For those that fail the second AED, a third AED
will be tried, and so on. Subjects who fail to gain control of
their seizures through the use of AEDs are commonly referred to as
"medically refractory." This creates a scenario in which 750,000
subjects or more in the United States have uncontrolled epilepsy.
These medically refractory subjects account for 80% of the $12.5
billion in indirect and direct costs that are attributable to
epilepsy in the United States.
[0010] A major challenge for physicians treating epileptic subjects
is gaining a clear view of the effect of a medication or
incremental medications. Presently, the standard metric for
determining efficacy of the medication is for the subject or for
the subject's caregiver to keep a diary of seizure activity.
However, it is well recognized that such self-reporting is often of
poor quality because subjects often do not realize when they have
had a seizure, or fail to accurately record seizures.
[0011] If a subject is refractory to treatment with chronic usage
of medications, surgical treatment options may be considered. If an
identifiable seizure focus is found in an accessible region of the
brain, which does not involve "eloquent cortex" or other critical
regions of the brain, then resection is considered. If no focus is
identifiable, or there are multiple foci, or the foci are in
surgically inaccessible regions or involve eloquent cortex, then
surgery is less likely to be successful or may not be indicated.
Surgery is effective in more than half of the cases, in which it is
indicated, but it is not without risk, and it is irreversible.
Because of the inherent surgical risks and the potentially
significant neurological sequelae from resective procedures, many
subjects or their parents decline this therapeutic modality.
[0012] Some non-resective functional procedures, such as corpus
callosotomy and subpial transection, sever white matter pathways
without removing tissue. The objective of these surgical procedures
is to interrupt pathways that mediate spread of seizure activity.
These functional disconnection procedures can also be quite
invasive and may be less effective than resection.
[0013] An alternative treatment for epilepsy that has demonstrated
some utility is open loop Vagus Nerve Stimulation (VNS). This is a
reversible procedure which introduces an electronic device which
employs a pulse generator and an electrode to alter neural
activity. The vagus nerve is a major nerve pathway that emanates
from the brainstem and passes through the neck to control visceral
function in the thorax and abdomen. VNS uses open looped,
intermittent stimulation of the left vagus nerve in the neck in an
attempt to reduce the frequency and intensity of seizures. See
Fisher et al., "Reassessment: Vagus nerve stimulation for epilepsy,
A report of the Therapeutics and Technology Assessment Subcommittee
of the American Academy of Neurology," Neurology 1999; 53:666-669.
While not highly effective, it has been estimated that VNS reduces
seizures by an average of approximately 30-50% in about 30-50% of
subjects who are implanted with the device. Unfortunately, a vast
majority of the subjects who are outfitted with the Cyberonics.RTM.
VNS device still suffer from un-forewarned seizures and many
subjects obtain no benefit whatsoever.
[0014] Another recent alternative electrical stimulation therapy
for the treatment of epilepsy is deep brain stimulation (DBS).
Open-loop deep brain stimulation has been attempted at several
anatomical target sites, including the anterior nucleus of the
thalamus, the centromedian nucleus of the thalamus, and the
hippocampus. The results have shown some potential to reduce
seizure frequency, but the efficacy leaves much room for
improvement.
[0015] Another type of electrical stimulation therapy for the
treatment epilepsy has been proposed by NeuroPace, Inc., in which
an implanted device is designed to detect abnormal electrical
activity in the brain and respond by delivering electrical
stimulation to the brain.
[0016] There have also been a number of proposals described in the
patent literature regarding the use of predictive algorithms that
purportedly can predict the onset of a seizure. When the predictive
algorithm predicts the onset of a seizure, some type of warning is
provided to the subject regarding the oncoming seizure or some sort
of therapy is initiated. For example, see U.S. Pat. Nos. 3,863,625
to Viglione, 5,995,868 to Dorfineister/Osorio, and 6,658,287 to
Litt et al., the complete disclosures of which are incorporated
herein by reference, describe a variety of proposed seizure
prediction systems. However, to date, none of the proposed seizure
prediction systems have shown statistically significant
results.
[0017] While most seizures are short-lasting events that last only
a few minutes, the seemingly random nature of the occurrence of
seizures is what overshadows and destroys a subject's quality of
life.
SUMMARY
[0018] Systems and methods for monitoring a patient are provided.
The system includes: an implantable sensor adapted to collect
neurological signals; an implantable assembly configured to sample
the neurological signals collected by the sensor; and a
rechargeable external assembly configured to wirelessly receive the
sampled neurological signals from the implantable assembly, said
external assembly being further configured to record a patient
entry in response to receiving an input from the patient. The
method includes: collecting neurological signals with a sensor
implanted in the patient; sampling the neurological signals
collected by the sensor with an implantable assembly implanted in
the patient; and transmitting the sampled neurological signals from
the implantable assembly to a rechargeable external assembly
external to the patient; and recording a patient entry in response
to receiving an input from the patient.
[0019] Also provided are methods and systems for sampling one or
more physiological signals from the subject and processing such
physiological signal(s) to monitor a subject's susceptibility or
for a future neurological event. Such systems may also be adapted
to provide an indication to the subject of their susceptibility for
the neurological event, such as a warning or instruction,
automatically initiate delivery of therapy to the subject, or allow
or instruct the subject or a caregiver to administer a therapy
prior to the onset of the seizure.
[0020] In preferred embodiments, the present invention is for
managing epilepsy. Managing epilepsy includes the prevention or
reduction of the occurrence of epileptic seizures and/or mitigating
their effects, as well as alerting a subject when their
susceptibility for having a seizure has been determined to be low.
The method of preventing an epileptic seizure comprises
characterizing a subject's susceptibility or susceptibility for a
future seizure, and upon the determination that the subject has an
elevated susceptibility for the seizure, communicating to the
subject and/or a health care provider a warning or a therapy
recommendation and/or initiating a therapy.
[0021] In one embodiment, the present invention provides ambulatory
data collection systems and methods. The data collection systems of
the present invention typically include one or more electrodes for
sampling one or more physiological signals from the subject. In
some embodiments, it may be desirable to include microelectrodes.
In preferred embodiment, the physiological signals include signals
that are indicative of neural activity in at least one portion of
the brain, such as intracranial EEG ("iEEG" or "ECoG"), EEG, or a
combination thereof. The electrodes may be intracranial electrodes
(e.g., epidural, subdural, depth electrodes), extracranial
electrodes (e.g., spike or bone screw electrodes, subcutaneous
electrodes, scalp electrodes, dense array (256 channels)
electrodes, etc.), or a combination thereof. While it is preferred
to monitor signals directly from the brain, it may also be
desirable to monitor brain activity using sphlenoidal electrodes,
foramen ovale electrodes, intravascular electrodes, peripheral
nerve electrodes, cranial nerve electrodes, or the like. While the
remaining disclosure focuses on intracranial electrodes, it should
be appreciated that any type of electrodes may be used to sample
signals from the subject.
[0022] The one or more electrodes are typically in communication
with an implanted assembly. The one or more electrodes may
communicate with the implanted assembly (or directly with the
external assembly as described below) with a wireless link, a wired
link, or both. The implanted assembly is typically configured to
facilitate transmission of a data signal that is representative of
the one or more sampled physiological signals. The implanted
assembly may be in wireless communication with an external assembly
using any type of known uni-directional or bi-directional wireless
link. Transmission of data and/or control signals between
implantable assembly and the external assembly is typically carried
out through a radiofrequency link, but may also be carried out
through telemetry, magnetic induction, electromagnetic link,
Bluetooth.RTM. link, Zigbee link, sonic link, optical link, other
types of conventional wireless links, or combinations thereof.
[0023] In one embodiment, the external assembly will typically be
configured to establish a one-way or two-way communication link
with the implanted assembly using conventional telemetry
handshaking protocols. The external assembly may allow the subject
(or the subject's physician) to adjust parameters of the sampling
of the physiological signal--such as adjusting the sampling rate,
the data transmission rate, error correction, sampled channels,
signal conditioning parameters (gain, filtering bandwidth, etc.),
the type of data that is stored, or the like. In some embodiments,
the implanted assembly will transmit a data signal that includes
raw or processed physiological signal (e.g., intracranial EEG, EEG,
etc.), one or more features that are extracted from the one or more
signals, a signal that is indicative of a communication that is
provided to the subject (e.g., warning, therapy recommendation,
etc.) or a combination thereof.
[0024] At least one of the implanted assembly and external assembly
may have a memory sub-system for storing data that is
representative of the one or more physiological signals that are
sampled with the one or more electrodes. In preferred embodiments,
the data is stored in the memory sub-system of the external
assembly. The data stored in the memory sub-system of the external
assembly may thereafter be transferred to a FLASH drive, hard
drive, a local computer, or to a remote server or computer system
through a network connection (e.g., local area network (LAN), wide
area network (WAN), the Internet, or the like). Preferably, the
data will be transmitted to the subject's physician or computer
station that is running software that can analyze the subject's
physiological signals.
[0025] In some embodiments, at least one of the implanted assembly
and external assembly will include one or more algorithms for
analyzing the sampled physiological signal in real time. Such
algorithms may be used as a seizure advisory system that is
configured to measure the subject's susceptibility for having a
neurological symptom. The systems of the present invention will
comprise similar elements as the data collection system described
above to facilitate sampling of EEG signals (and/or other
physiological signals) from the subject that are indicative of the
subject's susceptibility to seizure. The EEG signals may be
analyzed by one or more analysis algorithms to determine when a
subject is in an ictal state, a pro-ictal state or a contra-ictal
state. An "ictal state" is used herein to refer to a seizure. The
term "pro-ictal" is used herein to refer to a neurological state or
condition characterized by an increased likelihood or higher
susceptibility of transitioning to an ictal state. The term
"contra-ictal" is used herein to refer to a neurological state or
condition characterized by a low likelihood or susceptibility of
transitioning to an ictal state and/or a pro-ictal state within a
predetermined period of time. A more complete description of
pro-ictal, contra-ictal and ictal states are described in
co-pending and commonly owned patent application Ser. No.
12/020,450, filed Jan. 25, 2008, to Snyder et al., entitled
"Systems and Methods for Identifying a Contra-ictal Condition in a
Subject," the complete disclosure of which is incorporated herein
by reference.
[0026] In one embodiment, a subject's susceptibility for a seizure
can be estimated or derived from a neural condition which can be
characterized as a point along a single or multi-variable state
space continuum. The term "neural state" is used herein to
generally refer to calculation results or indices that are
reflective of the state of the subject's neural system, but does
not necessarily constitute a complete or comprehensive accounting
of the subject's total neurological condition. The estimation and
characterization of "neural state" may be based on one or more
subject dependent parameters from the brain, such as electrical
signals from the brain, including but not limited to
electroencephalogram signals "EEG" and electrocorticogram signals
"ECoG" or intracranial EEG (referred to herein collectively as
EEG''), brain temperature, blood flow in the brain, concentration
of AEDs in the brain or blood, etc.), heart rate, respiratory rate,
chemical concentrations, etc.
[0027] The algorithms may analyze the sampled EEG signals in the
implanted assembly, in the external assembly, or a portion of the
advisory algorithm may be in both the implanted assembly and the
external assembly. If the seizure advisory algorithm determines
that the subject has entered a pro-ictal condition, the external
assembly may be used to provide a warning, instruction, or other
output to the subject that informs them of their transitioning from
an inter-ictal or normal condition to the pro-ictal condition. The
output from the external assembly may be visual, audio, tactile
(e.g., vibratory), or some combination thereof. Such outputs from
the external assembly may allow the user to make themselves safe
(e.g., stop cooking, pull to the side of the road when driving, lie
down, etc.) prior to the onset of the actual seizure or allow the
subject to take an acute dosage of an AED to prevent or mitigate
the seizure. Most importantly, the subject's will no longer be
surprised by the seizures and will have more control over their
life.
[0028] Such algorithms may also be used to provide insight to the
subject and the subject's physician regarding the subject's
specific seizure triggers. For example, if the subject's
susceptibility to a seizure increases (and a warning is given)
every time the subject intakes alcohol or a specific food, is sleep
deprived, or is subject to a certain stimulus, the subject may be
able to learn which triggers to avoid. Consequently, such seizure
advisory systems will be able to provide quantifiable data to the
subject and their physician regarding the subject-specific seizure
triggers.
[0029] The seizure detection algorithm(s) may be used to detect the
electrographic seizure onset and provide a seizure warning to the
subject (or a care giver) just prior to the clinical manifestation
of the seizure. Such a warning may or may not be sufficient to
allow the subject to stop the seizure from occurring, but at a
minimum, the warning will provide the subject or caregiver many
seconds (or minutes) prior to the onset of the clinical seizure and
allow the subject and/or caregiver to make the subject safe.
[0030] The systems described herein can also include an alert that
is configured to indicate that there is a communication error
between the implanted assembly and the external assembly. The alert
can be disposed either in the internal assembly or in the external
assembly. The alert can be a visible alert, an audible alert, a
tactile alert, or any combination thereof.
[0031] The communication error can be a single type of
communication error, or it can be a combination of different types
of communication errors. For example, the communication error can
be that the external assembly is out of communication range with
the implanted assembly such that the external assembly is not
receiving a data signal from the implanted device. The
communication error can be that the external assembly is out of
communication range with the implanted assembly for a predetermined
amount of time. The communication error can be that the external
assembly not receiving the data signal at an expected time or
within an expected period of time. The external assembly can be
configured to expect to receive a substantially continuous data
signal, or the external assembly can be programmed to expect to
receive a data signal periodically. The communication error can be
that there is a gap in a data signal communication stream, such as
missing packets of data in a numbered sequence of packets. The
communication error can also be a data formatting error, such as an
invalid cyclic redundancy. If the system detects a communication
error an alert will be activated to indicate there is a
communication error.
[0032] The systems that provide an alert when there is a
communication error between the implanted assembly and the external
assembly can also include an input on the external assembly that
allows the subject to deactivate an alert function when the subject
has a low likelihood of transitioning into the seizure condition,
such as a contra-ictal condition. An alarm deactivation period can
be less than a time period in which the subject is unlikely to
transition into the seizure condition. In one example, the
deactivation period is 45 minutes and the time period in which the
subject is unlikely to transition into the seizure condition is 60
minutes. The deactivation period can be adjustable by the subject
up to a maximum time period that does not exceed the time period in
which the subject is unlikely to transition into the seizure
condition.
[0033] Another aspect of the invention is a seizure advisory
device. The seizure advisory device includes a user interface that
comprises an indicator that indicates if the subject is at a low
susceptibility to a seizure or a high susceptibility to a seizure.
The seizure advisory device also includes an alert that is
configured to provide an indication, such as an audible output, to
the subject if the seizure advisory device is out of communication
range with an implantable telemetry unit and is unable to
accurately communicate the subject's susceptibility to the
seizure.
[0034] One aspect of the invention is a method of activating an
alert when there is a communication error between an implantable
device and a device external to a subject. The method includes
sampling a brain activity signal from a subject, transmitting a
data signal indicative of the sampled brain activity signal from an
implanted assembly to an external assembly outside of the subject,
and activating an alert when there is a communication error between
the implanted assembly and the external assembly. The method can
include storing the data signal in the implanted assembly if there
is a communication error, as well as attempting to retransmit the
data signal after the error is detected.
[0035] One aspect of the invention is a method of informing a
subject when a seizure advisory device is out of communication
range with an implantable device. The method includes receiving a
transcutaneously transmitted data signal indicative of the sampled
brain activity signal from an implanted device and activating an
alert when an expected data signal transmitted from the implanted
device is not received by the seizure advisory device. The seizure
advisory device can be configured to analyze the data signal to
estimate the subject's susceptibility to a seizure. Alternatively,
the implanted device is configured to analyze the data signal to
estimate the subject's susceptibility to a seizure and the seizure
advisory device is configured to communicate the estimated
susceptibility to the subject. The data signal can be transmitted
substantially continuously and comprises substantially real-time
sampled brain activity signals.
[0036] The seizure advisory systems of the present invention may be
used in conjunction with a therapy that may prevent the seizure
from occurring, reduce the severity of the oncoming seizure, reduce
the duration of the oncoming seizure, or the like. The therapy may
be initiated in a closed loop within the system, or the therapy may
be manually initiated by the subject or caregiver.
[0037] Depending on the level of the subject's susceptibility for a
seizure, the output provided to the subject may take a variety of
different forms. Some embodiments will provide an output to the
subject that causes the subject to take an acute dosage of a
pharmacological agent (e.g., neuro-suppressant, sedative such as a
rapid onset benzodiazepine, AED or anticonvulsant, or other
medication which exhibits seizure prevention effects). The advisory
algorithm(s) may be used to characterize the subject's
susceptibility for a future seizure. If the advisory algorithm
determines that the subject is at an increased or elevated
susceptibility for a future seizure, the system may provide an
output to the subject and/or caregiver that facilitates the subject
to take or the caregiver to provide an acute dosage of a
pharmacological agent (such as an AED) to prevent the occurrence of
the seizure or reduce the magnitude or duration of the seizure.
[0038] As used herein, the term "anti-epileptic drug" or "AED"
generally encompasses pharmacological agents that reduce the
frequency or susceptibility of a seizure. There are many drug
classes that comprise the set of AEDs, and many different
mechanisms of action are represented. For example, some medications
are believed to increase the seizure threshold, thereby making the
brain less likely to initiate a seizure. Other medications retard
the spread of neural bursting activity and tend to prevent the
propagation or spread of seizure activity. Some AEDs, such as the
benzodiazepines, act via the GABA receptor and globally suppress
neural activity. However, other AEDs may act by modulating a
neuronal calcium channel, a neuronal potassium channel, a neuronal
NMDA channel, a neuronal AMPA channel, a neuronal metabotropic type
channel, a neuronal sodium channel, and/or a neuronal kainite
channel.
[0039] Unlike conventional anti-epileptic drug treatments, which
provide for an "open loop" chronic regimen of pharmacological
agents, the present invention is able to manage seizures acutely
while substantially optimizing the intake of the pharmacological
agent by having the subject to take a pharmacological agent only
when it is determined that the subject has transitioned to a higher
susceptibility to a seizure, e.g., to a pro-ictal condition.
Furthermore, with this new paradigm of seizure prevention, the
present invention provides a new indication for pharmacotherapy.
This new indication is served by several existing medications,
including AEDs, given at doses which are sub-therapeutic to their
previously known indications, such as acute AED administration for
seizure termination or status epilepticus. Since this new
indication is served by a new and much lower dosing regimen and
consequently a new therapeutic window, the present invention is
able to provide a correspondingly new and substantially reduced
side effect profile and may reduce or eliminate tolerance effects
of the AED. For example, the present invention allows the use of
dosages that are lower than FDA-approved dosages for the various
anti-epileptic agents. This dosing may be about 5% to about 95%
lower than the FDA-recommended dose for the drug, and preferably at
or below 90% of the FDA-recommended dose, and most preferably below
about 50% of the FDA-recommended dose. But as can be appreciated,
if the measured signals indicate a high susceptibility for a
seizure, the methods and systems of the present invention may
recommend taking an FDA or a higher than FDA approved dose of the
AED to prevent the seizure. Such a paradigm has valuable
application for subjects in which side effects of AEDs are
problematic, particular sedation in general and teratogenicity in
pregnant women or risk of teratogenicity in all women of child
bearing age. A more complete description of using acute dosages of
AEDs with a seizure advisory system is described in commonly owned
U.S. patent application Ser. Nos. 11/321,897, 11/321,898, and
11/322,150 (all filed Dec. 28, 2005), the complete disclosures of
which are incorporated herein by reference.
[0040] In another embodiment, the present invention provides a
system that comprises an advisory algorithm that may be used to
modify or alter the scheduling and/or dosing of a chronically
prescribed pharmacological agent, such as an AED, to optimize or
custom tailor the dosing to a particular subject at a particular
point in time. This allows for (1) improved efficacy for individual
subjects, since there is variation of therapeutic needs among
subjects, and (2) improved response to variation in therapeutic
needs for a given subject with time, resulting form normal
physiological variations as well as from external and environmental
influences, such as stress, sleep deprivation, the presence of
flashing lights, alcohol intake and withdrawal, menstrual cycle,
and the like. The advisory algorithm may be used to characterize
the subject's susceptibility for the future seizure. If the
advisory algorithm determines that the subject is at an elevated
susceptibility for an epileptic seizure or otherwise predicts the
onset of a seizure, the system may provide an output that indicates
or otherwise recommends or instructs the subject to take an
accelerated or increased dosage of a chronically prescribed
pharmacological agent. Consequently, the present invention may be
able to provide a lower chronic plasma level of the AED and
modulate the intake of the prescribed agent in order to decrease
side effects and maximize benefit of the AED.
[0041] The seizure advisory systems of the present invention may be
used by medically refractory subjects as well as by subjects who
are chronically administering one or more AEDs. Advantageously,
such a system may be used to titrate the chronic medications to a
level that reduces the side effects, while still providing seizure
prevention effects. If the seizure advisory systems of the present
invention are able to determine that the subject has a high
susceptibility with time periods that are longer than the time for
the AED to reach a threshold plasma level and prevent the onset of
the seizure, the subject may be able to take supplementary dosage
of medication that is administered in response to the assessment of
the higher susceptibility to the seizure. Such a method would
reduce the subject's overall chronic intake of AEDs, while still
preventing seizures in the subject.
[0042] The supplementary dosages may be the subject's standard
dosage, a larger than standard dosage, or a smaller than standard
dosage. The supplementary dosage could be the same AED that the
subject takes chronically, or it could be a different AED. It may
be desirable to have the dosage and/or type of medication be
variable based on the ability of the algorithms to assess the
particular subject's neurological condition. While the above
description focuses on subject-administered AEDs, the systems of
the present invention also encompass the use of implanted drug
pumps that be automatically initiated by a control signal from the
implanted assembly and/or the external assembly. Such implanted
drug pumps may use similar dosing schemes as described above.
[0043] In other embodiments, the present invention provides seizure
advisory systems in conjunction with automated or manual actuation
of electrical neuromodulation. The electrical neuromodulation may
be delivered to a peripheral nerve (e.g., vagus nerve stimulation
("VNS")), a cranial nerve (e.g., trigeminal nerve stimulation
("TNS")), directly to the brain tissue (e.g., deep brain
stimulation (DBS), cortical stimulation, etc.), or any combination
thereof.
[0044] In one configuration, the seizure advisory systems of the
present invention may be used in conjunction with an existing
implanted Cyberonics.RTM. VNS system. If the seizure advisory
system of the present invention determines that the subject has
transitioned to a pro-ictal condition, the system may provide an
output to the subject so as to inform the subject to activate the
VNS device with a wand. In alternative embodiments, the implanted
assembly may include an integrated pulse generator that is
configured to generate the neuromodulation signal that is delivered
to a vagus nerve electrode.
[0045] Advantageously, the systems and methods of the present
invention may be used to reduce subject anxiety and restore a sense
of control in the subject's life, stop or reduce the duration or
severity of the seizures, reduce or eliminate physical injuries to
the subject, potentially increase vocational opportunities by
allowing epileptic subjects to hold down jobs they wouldn't
otherwise be able to have, resume their driving privileges,
increase comfort with social interaction, and enable certain key
activities of daily living.
[0046] For a further understanding of the nature and advantages of
the present invention, reference should be made to the following
description taken in conjunction with the accompanying
drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0047] The novel features of the invention are set forth with
particularity in the appended claims. A better understanding of the
features and advantages of the present invention will be obtained
by reference to the following detailed description that sets forth
illustrative embodiments, in which the principles of the invention
are utilized, and the accompanying drawings of which:
[0048] FIG. 1 illustrates one embodiment of a monitoring or data
collection system which comprises one or more intracranial
electrodes in communication with an external assembly through an
implanted assembly.
[0049] FIG. 2 illustrates examples of electrode arrays that may be
used with the system of FIG.
[0050] FIG. 3 is a simplified illustration of an implanted assembly
that may be used with the system of FIG. 1.
[0051] FIG. 4 is a simplified illustration of a method of alerting
a subject of a communication error between the implanted assembly
and external assembly.
[0052] FIG. 5 is a simplified illustration of an external assembly
that may be used with the system of FIG. 1.
[0053] FIG. 6 is an alternative illustration of an external
assembly that may be used with the system.
[0054] FIG. 7 illustrates an exemplary user interface including
outputs of an exemplary external assembly that may be used with the
system.
[0055] FIG. 8 illustrates an exemplary external assembly that may
be used with the system.
[0056] FIG. 9 is a simplified flow chart that illustrates one
method of storing EEG data.
[0057] FIG. 10 illustrates a method of measuring seizure activity
data for clinical and/or sub-clinical seizures.
[0058] FIG. 11 illustrates a method of evaluating efficacy of a
therapy.
[0059] FIG. 12 illustrates a method of titrating an efficacious
therapy.
[0060] FIG. 13 illustrates one embodiment of a simplified seizure
advisory system which comprises an array of epidural or subdural
electrodes and an array of depth electrodes in communication with
an external assembly through an implanted assembly.
[0061] FIG. 14 schematically illustrates a plurality of algorithms
that may be embodied by the present invention.
[0062] FIG. 15 illustrates a method of using a seizure advisory
system.
[0063] FIG. 16 illustrates another variation to the system of FIG.
6 which includes a pulse generator that is coupled to a vagus nerve
electrode array.
[0064] FIG. 17 illustrates a separate vagus nerve stimulator that
is used in conjunction with a seizure advisory system.
DETAILED DESCRIPTION OF THE INVENTION
[0065] Certain specific details are set forth in the following
description and figures to provide an understanding of various
embodiments of the invention. Certain well-known details,
associated electronics and devices are not set forth in the
following disclosure to avoid unnecessarily obscuring the various
embodiments of the invention. Further, those of ordinary skill in
the relevant art will understand that they can practice other
embodiments of the invention without one or more of the details
described below. Finally, while various processes are described
with reference to steps and sequences in the following disclosure,
the description is for providing a clear implementation of
particular embodiments of the invention, and the steps and
sequences of steps should not be taken as required to practice this
invention.
[0066] The term "condition" is used herein to generally refer to
the subject's underlying disease or disorder--such as epilepsy,
depression, Parkinson's disease, headache disorder, etc. The term
"state" is used herein to generally refer to calculation results or
indices that are reflective a categorical approximation of a point
(or group of points) along a single or multi-variable state space
continuum of the subject's condition. The estimation of the
subject's state does not necessarily constitute a complete or
comprehensive accounting of the subject's total situation. As used
in the context of the present invention, state typically refers to
the subject's state within their neurological condition. For
example, for a subject suffering from an epilepsy condition, at any
point in time the subject may be in a different states along the
continuum, such as an ictal state (a state in which a neurological
event, such as a seizure, is occurring), a pro-ictal state (a state
in which the subject has an increased risk of transitioning to the
ictal state), an inter-ictal state (a state in between ictal
states), a contra-ictal state (a state in which the subject has a
low risk of transitioning to the ictal state within a calculated or
predetermined time period), or the like. A pro-ictal state may
transition to either an ictal or inter-ictal state.
[0067] The estimation and characterization of "state" may be based
on one or more subject dependent parameters from a portion of the
subject's body, such as electrical signals from the brain,
including but not limited to electroencephalogram signals and
electrocorticogram signals "ECoG" or intracranial EEG (referred to
herein collectively as "EEG"), brain temperature, blood flow in the
brain, concentration of AEDs in the brain or blood, changes
thereof, etc. While parameters that are extracted from brain-based
signals are preferred, the present invention may also extract
parameters from other portions of the body, such as the heart rate,
respiratory rate, blood pressure, chemical concentrations, etc.
[0068] An "event" is used herein to refer to a specific event in
the subject's condition. Examples of such events include transition
from one state to another state, e.g., an electrographic onset of
seizure, end of seizure, or the like. For conditions other than
epilepsy, the event could be an onset of a migraine headache, onset
of a depressive episode, a tremor, or the like.
[0069] The occurrence of a seizure may be referred to as a number
of different things. For example, when a seizure occurs, the
subject is considered to have exited a "pro-ictal state" and has
transitioned into the "ictal state". However, the electrographic
onset of the seizure (one event) and/or the clinical onset of the
seizure (another event) have also occurred during the transition of
states.
[0070] A subject's "susceptibility" for a seizure is a measure of
the likelihood of transitioning into the ictal state. The subject's
susceptibility for seizure may be estimated by determining which
"state" the subject is currently in. As noted above, the subject is
deemed to have an increased susceptibility for transitioning into
the ictal state (e.g., have a seizure) when the subject is
determined to be in a pro-ictal state. Likewise, the subject may be
deemed to have a low susceptibility for transitioning into the
ictal state when it is determined that the subject is in a
contra-ictal state.
[0071] While the discussion below focuses on measuring electrical
signals generated by electrodes placed near, on, or within the
brain or nervous system (EEG signals) of subjects and subject
populations for the determination of a subject's susceptibility for
having a seizure, it should be appreciated that the invention is
not limited to measuring EEG signals or to determining the
subject's susceptibility for having a seizure. For example, the
invention could also be used in systems that measure one or more of
a blood pressure, blood oxygenation indicator e.g. via pulse
oximetry, temperature of the brain or of portions of the subject,
blood flow measurements, ECG/EKG, heart rate signals, respiratory
signals, chemical concentrations of neurotransmitters, chemical
concentrations of medications, pH in the blood, or other
physiological or biochemical parameters of a subject.
[0072] Furthermore, while the remaining discussion focuses on
systems and method for measuring a subject's susceptibility for
having a seizure, the present invention may also be applicable to
monitoring other neurological or psychiatric disorders and
determining the susceptibility for such disorders. For example, the
present invention may also be applicable to monitoring and
management of sleep apnea, Parkinson's disease, essential tremor,
Alzheimer's disease, migraine headaches, depression, eating
disorders, cardiac arrhythmias, bipolar spectrum disorders, or the
like. The present invention may also be applicable to non-medical
monitoring and management of events such as storms, earthquakes,
social unrest, or other episodic events from which identification
of a low susceptibility state may be useful. As can be appreciated,
the features extracted from the signals and used by the algorithms
will be specific to the underlying disorder that is being managed.
While certain features may be relevant to epilepsy, such features
may or may not be relevant to the state measurement for other
disorders.
[0073] The devices and systems of the present invention can be used
for long-term, ambulatory sampling and analysis of one or more
physiological signals, such as a subject's brain activity (e.g.,
EEG). In many embodiments, the systems and methods of the present
invention incorporate brain activity analysis algorithms that
extract one or more features from the brain activity signals
(and/or other physiological signals) and classifies, or otherwise
processes, such features to determining the subject's
susceptibility for having a seizure.
[0074] Some systems of the present invention may also be used to
facilitate delivery of a therapy to the subject to prevent the
onset of a seizure and/or abort or mitigate a seizure. Facilitating
the delivery of the therapy may be carried out by outputting a
warning or instructions to the subject or automatically initiating
delivery of the therapy to the subject (e.g., pharmacological,
electrical stimulation, focal cooling, etc.). The therapy may be
delivered to the subject using an implanted assembly that is used
to collect the ambulatory signals, or it may be delivered to the
subject through a different implanted or external assembly.
[0075] A description of some systems that may be used to delivery a
therapy to the subject are described in commonly owned U.S. Pat.
Nos. 6,366,813 and 6,819,956, U.S. Patent Application Publication
Nos. 2005/0021103 (published Jan. 27, 2005), 2005/0119703
(published Jun. 2, 2005), 2005/0021104 (published Jan. 27, 2005),
2005/0240242 (published Oct. 27, 2005), 2005/0222626 (published
Oct. 6, 2005), and U.S. patent application Ser. Nos. 11/282,317
(filed Nov. 17, 2005), 11/321,897, 11/321,898, and 11/322,150 (all
filed Dec. 28, 2005), the complete disclosures of which are
incorporated herein by reference.
[0076] For subjects suspected or known to have epilepsy, the
systems of the present invention may be used to collect data and
quantify metrics for the subjects that heretofore have not been
accurately measurable. For example, the data may be analyzed to (1)
determine whether or not the subject has epilepsy, (2) determine
the type of epilepsy, (3) determine the types of seizures, (4)
localize or lateralize one or more seizure foci or seizure
networks, (5) assess baseline seizure statistics and/or change from
the baseline seizure statistics (e.g., seizure count, frequency,
duration, seizure pattern, etc.), (6) monitor for sub-clinical
seizures, assess a baseline frequency of occurrence, and/or change
from the baseline occurrence, (7) measure the efficacy of AED
treatments, deep brain or cortical stimulation, peripheral nerve
stimulation, and/or cranial nerve stimulation, (8) assess the
effect of adjustments of the parameters of the AED treatment, (9)
determine the effects of adjustments of the type of AED, (10)
determine the effect of, and the adjustment to parameters of,
electrical stimulation (e.g., peripheral nerve stimulation, cranial
nerve stimulation, deep brain stimulation (DBS), cortical
stimulation, etc.), (11) determine the effect of, and the
adjustment of parameters of focal cooling (e.g., use of cooling
fluids, peltier devices, etc., to diminish or reduce seizures (see,
for example, "Rothman et al., "Local Cooling: A Therapy for
Intractable Neocortical Epilepsy," Epilepsy Currents, Vol. 3, No.
5, September/October 2003; pp. 153-156, (12) determine "triggers"
for the subject's seizures, (13) assess outcomes from surgical
procedures, (14) provide immediate biofeedback to the subject, (15)
screen subjects for determining if they are an appropriate
candidate for a seizure advisory system or other neurological
monitoring or therapy system, or the like.
[0077] In a first aspect of the invention, the present invention
encompasses a data collection system that is adapted to collect
long term ambulatory brain activity data from the subject. In
preferred embodiments, the data collection system is able to sample
one or more channels of brain activity from the subject with one or
more implanted electrodes. The electrodes are in wired or wireless
communication with one or more implantable assemblies that are, in
turn, in wired or wireless communication with an external assembly.
The sampled brain activity data may be stored in a memory of the
implanted assembly, external assembly and/or a remote location such
as a physician's computer system. In alternative embodiments, it
may be desirable to integrate the electrodes with the implanted
assembly, and such an integrated implanted assembly may be in
communication with the external assembly.
[0078] Unlike other conventional systems which have an implanted
memory that is able to only store small epochs of brain activity
before and after a seizure, the implantable assemblies of the
present invention are configured to substantially continuously
sample the physiological signals over a much longer time period
(e.g., anywhere between one day to one week, one week to two weeks,
two weeks to a month, or more) so as to be able to monitor
fluctuations of the brain activity (or other physiological signal)
over the entire time period. In alternative embodiments, however,
the implantable assembly may only periodically sample the subject's
physiological signals or selectively/aperiodically monitor the
subject's physiological signals. Some examples of such alternative
embodiments are described in commonly owned U.S. patent application
Ser. Nos. 11/616,788 and 11/616,793, both filed Dec. 27, 2006, the
complete disclosures of which are incorporated herein by
reference.
[0079] When the memory is almost full, the system may provide the
subject a warning so that the subject may manually initiate
uploading of the collected brain activity data or the system may
automatically initiate a periodic download of the collected brain
activity data from a memory of the external assembly to a hard
drive, flash-drive, local computer workstation, remote server or
computer workstation, or other larger capacity memory system. In
alternative embodiments, the external assembly may be configured to
automatically stream the stored EEG data over a wireless link to a
remote server or database. Such a wireless link may use existing
WiFi networks, cellular networks, pager networks or other wireless
network communication protocols. Advantageously, such embodiments
would not require the subject to manually upload the data and could
reduce the down time of the system and better ensure permanent
capture of substantially all of the sampled data.
[0080] Another aspect of the invention is a system for monitoring a
subject's susceptibility, or susceptibility, to a seizure. The
system includes an electrode and an implanted communication
assembly in communication with the electrode. The implanted
communication assembly samples a neural signal with the electrode
and substantially continuously transmits a data signal from the
subject's body. The system also comprises an external assembly
positioned outside the subject's body that is configured to receive
and process the data signal to measure the subject's susceptibility
to having a seizure. In alternative embodiments the implanted
assembly processes the data and measures the subject's
susceptibility of having a seizure, in which case only data
indicative of the measured susceptibility is transmitted to the
external assembly.
[0081] FIG. 1 illustrates an exemplary embodiment of a either a
data collection system or monitoring system as described herein.
System 10 includes one or more electrode arrays 12 that are
configured to be implanted in the subject and configured to sample
electrical activity from the subject's brain. The electrode array
12 may be positioned anywhere in, on, and/or around the subject's
brain, but typically one or more of the electrodes are implanted
within in the subject. For example, one of more of the electrodes
may be implanted adjacent or above a previously identified
epileptic network, epileptic focus or a portion of the brain where
the focus is believed to be located. While not shown, it may be
desirable to position one or more electrodes in a contralateral
position relative to the focus or in other portions of the
subject's body to monitor other physiological signals.
[0082] The electrode arrays 12 of the present invention may be
intracranial electrodes (e.g., epidural, subdural, and/or depth
electrodes), extracranial electrodes (e.g., spike or bone screw
electrodes, subcutaneous electrodes, scalp electrodes, dense array
electrodes), or a combination thereof. While it is preferred to
monitor signals directly from the brain, it may also be desirable
to monitor brain activity using sphlenoidal electrodes, foramen
ovale electrodes, intravascular electrodes, peripheral nerve
electrodes, cranial nerve electrodes, or the like. While the
remaining disclosure focuses on intracranial electrodes for
sampling intracranial EEG, it should be appreciated that the
present invention encompasses any type of electrodes that may be
used to sample any type of physiological signal from the
subject.
[0083] In the configuration illustrated in FIG. 1, two electrode
arrays 12 are positioned in an epidural or subdural space, but as
noted above, any type of electrode placement may be used to monitor
brain activity of the subject. For example, in a minimally invasive
embodiment, the electrode array 12 may be implanted between the
skull and any of the layers of the scalp. Specifically, the
electrodes 12 may be positioned between the skin and the connective
tissue, between the connective tissue and the epicranial
aponeurosis/galea aponeurotica, between the epicranial
aponeurosis/galea aponeurotica and the loose aerolar tissue,
between the loose aerolar tissue and the pericranium, and/or
between the pericranium and the calvarium. To improve
signal-to-noise ratio, such subcutaneous electrodes may be rounded
to conform to the curvature of the outer surface of the cranium,
and may further include a protuberance that is directed inwardly
toward the cranium to improve sampling of the brain activity
signals. Furthermore, if desired, the electrode may be partially or
fully positioned in openings disposed in the skull. Additional
details of exemplary wireless minimally invasive implantable
devices and their methods of implantation can be found in U.S.
application Ser. No. 11/766,742, filed Jun. 21, 2007, the
disclosure of which is incorporated by reference herein in its
entirety.
[0084] Some exemplary configurations of the electrode arrays 12 are
shown in FIG. 2. Each of the illustrated electrode arrays has eight
electrode contacts so as to provide sixteen 16 channels for
monitoring the EEG signals. The electrode contacts may be bipolar
or referential. It should be appreciated however, that while FIG. 2
illustrates sixteen 16 channels that are distributed over two
electrode arrays, any number electrode arrays that have any number
of contacts may be used with the present invention. In most
embodiments, however, the system typically includes between about 1
and about 256 channels, and preferably between about 1 and about 32
channels, and more preferably between 8 and 32 channels that are
distributed over 1 array and about 4 arrays. The array pattern and
number of contacts on each array may be configured in any desirable
pattern.
[0085] FIG. 2 specifically illustrates a 2.times.4 grid electrode
array 30, a 1.times.8 strip electrode array 32, or a 1.times.8
depth electrode array 34. Each of the electrode arrays 12 will be
coupled to the implanted assembly 14 with leads 16, unless they are
wireless leads. The leads of each of the electrode arrays 12 will
typically have a common lead body 17 and connector 19. The
connector 19 may take any conventional or proprietary form, but in
preferred embodiments is based on SCS/ICD technology. The electrode
arrays could be used in either a bipolar or monopolar
configuration.
[0086] If the system 10 includes the capability of providing
stimulation of the peripheral nerve, such as the vagus nerve, the
system may include a vagus nerve cuff 36, which includes a modified
IS1 connector that is used for Cyberonics vagus nerve lead. The
systems 10 of the present invention may also be configured to
provide electrical stimulation to other portions of the nervous
system (e.g., cortex, deep brain structures, cranial nerves, etc.).
Stimulation parameters are typically about several volts in
amplitude, 50 microsec to 1 milisec in pulse duration, and at a
frequency between about 2 Hz and about 1000 Hz.
[0087] As shown in FIG. 1, the electrode arrays 12 are in wired
communication with an implanted assembly 14 via the wire leads 16.
The individual leads from the contacts (not shown) are placed in
lead 16 and the lead 16 is tunneled between the cranium and the
scalp and subcutaneously through the neck to the implanted assembly
14. Typically, implanted assembly 14 is implanted in a
sub-clavicular pocket in the subject, but the implanted assembly 14
may be disposed somewhere else in the subject's body. For example,
the implanted assembly 14 may be implanted in the abdomen or
underneath, above, or within an opening in the subject's cranium
(not shown).
[0088] Implanted assembly 14 can be used to pre-process EEG signals
sampled by the electrode array 12 and transmit a data signal that
is encoded with the sampled EEG data over a wireless link 18 to an
external assembly 20, where the EEG data is permanently or
temporarily stored. FIG. 3 illustrates a simplified embodiment of
an exemplary implanted assembly 14. Implanted assembly 14 may
comprise a cast epoxy packaging 40 that hermetically encapsulates
the sub-assemblies of the implanted assembly 14. In other
embodiments, the packaging 40 may include (i) biocompatible metals
such as platinum, niobium, titanium, tantalum, and various alloys
of these metals, (ii) biocompatible ceramics such as Aluminum Oxide
(Al.sub.2O.sub.3), Zirconium Oxide (ZO.sub.2), and Boron Nitride
(BN), (iii) and any combination of ceramic, metal, and epoxy. Some
examples of such embodiments are described in commonly owned U.S.
Provisional Patent Application No. 61/017,504, filed Dec. 28, 2007,
the complete disclosure of which is incorporated herein by
reference.
[0089] Packaging 40 is preferably as small as possible and may have
a similar packaging footprint as a spinal cord stimulator. Thus,
the packaging typically has a volume between about 10 cubic
centimeters to about 70 cubic centimeters and preferably about 30
cubic centimeters, but may be larger or smaller, depending on what
components are disposed therein. Packaging 40 comprises an
interface 41 for the connectors 19 of leads 16. The interface 41
will have at least the same number of input channels as the number
of contacts in the electrode array, and may have more input
channels than active contacts. Interface 41 may also have one or
more bipolar output channels for delivering electrical stimulation
to a peripheral nerve, brain tissue, cranial nerves, or other
portions of the subject's body. Further details of an exemplary
housing structure for the implanted assembly can be found in U.S.
Provisional Application No. 61/017,504, filed Dec. 28, 2007, the
disclosure of which is incorporated by reference herein in its
entirety.
[0090] The interconnections between the components of implanted
assembly 14 and external assembly 20 may be may be wired, wireless,
digital, analog, or any combination thereof, and such electronic
components may be embodied as hardware, software, firmware, or any
combination thereof. While FIG. 3 shows one preferred embodiment of
the electronic components of implanted assembly 14, it should be
appreciated that the functionality performed by each of the
sub-assemblies shown in FIG. 3 may be embodied in multiple
sub-assemblies and the functionality carried out by multiple
sub-assemblies of FIG. 3 may be combined into a single
sub-assembly. Furthermore, some embodiments of the implanted
assembly 14 may have additional functionalities not illustrated,
while other embodiments may not have all of the functionality
and/or electronic components that are illustrated in FIG. 3.
[0091] The electronic components of the implanted assembly will
typically comprise a signal conditioning sub-assembly 42 that
conditions the one or more EEG signals received from the interface
41. The signal conditioning sub-assembly 42 may perform
amplification, combined to reduce common mode signal, filtering
(e.g., lowpass, highpass, bandpass, and/or notch filtering),
digital-to-analog conversion, or some combination thereof.
[0092] The electronic components of the implanted assembly 14 may
optionally comprise dedicated circuitry and/or a microprocessor
(referred to herein collectively as "processing sub-assembly 44")
for further processing of the EEG signals prior to transmission to
the external assembly 20. The further processing may include any
combination of encryption, forward error correction, checksum or
cyclic redundancy checks (CRC), or the like. The processing
sub-assembly may comprise an ASIC, off the shelf components, or the
like. In one embodiment processing sub-assembly 44 includes one or
more multiple-core processors for processing data. Such
multiple-core microprocessors provide faster processing, while
consuming less power than multiple single core processors.
Consequently, the life of the power source 44 may be prolonged.
Some examples of suitable multiple-core processors include the
Intel.RTM. Core 2 Duo Processor and the AMD.RTM. dual-core Opteron
microprocessor.
[0093] Of course, while FIG. 3 illustrates a separate conditioning
assembly 42 and processing sub-assembly, the two assemblies may be
embodied in a single ASIC that performs the functionality of both
assemblies 42, 44.
[0094] The implanted assembly 14 will also typically include both a
clock 48 and a power source 50. The clock 48 is typically in the
form of an oscillator and frequency synthesizer to provide
synchronization and a time base for the signals transmitted from
internal assembly and for signals received from external assembly
20. Power source 50 may be a non-rechargeable battery, a
rechargeable battery, a capacitor, etc. One preferred power source
is a medical grade rechargeable Li-Ion battery that is commonly
used in other implantable devices. The rechargeable power source 50
may also be in communication with the communication sub-system 46
so as to receive power from outside the body by inductive coupling,
radiofrequency (RF) coupling, etc. Such rechargeable power sources
typically have a lifespan of between about 3 years and about 5
years. Power source 50 will generally be used to provide power to
the other components of the implantable assembly 14.
[0095] In some embodiments, the implanted assembly 14 may
optionally include a memory sub-system 52 (e.g., RAM) for
permanently or temporarily storing or buffering the processed EEG
signal. For example, memory sub-assembly 52 may be used as a buffer
to temporarily store the processed EEG data if there are problems
with transmitting the data to the external assembly. For example,
if the external assembly's power supply is low, the memory in the
external assembly is removed, or if the external assembly is out of
communication range with the implantable assembly 14, the EEG data
may be temporarily buffered in memory sub-assembly 52 and the
buffered EEG data and the current sampled EEG data may be
transmitted to the external assembly when the problem has been
corrected. The buffer may be any size, but it will typically be
large enough to store between about 1 megabyte and 100 megabytes of
data. As can be appreciated, as technology improves and the
capacity of memory cards improve, it is likely that many hundreds
of gigabytes or hundreds of gigabytes of data may be buffered in
the internal memory. Of course, in embodiments that do not have a
memory sub-system 52 in the implanted assembly 14, any data that is
sampled during the times in which the external assembly 20 is out
of communication range with the implanted assembly 14, there may
simply be gaps in the stored data.
[0096] In some embodiments the system 10 of the present invention
may incorporate an alert that is activated to indicate that there
is a communication error between the implanted assembly and the
external assembly. Exemplary communication errors include, without
limitation, when (1) the external assembly 20 is out of
communication range with the internal assembly 14 such that the
transmitted data signals are not received by the external assembly,
(2) there is some other error in the transmission and receipt of
data signals between the internal assembly 14 and external
assembly, (3) self test error has been encountered, (4) memory card
is full (or nearly full), or some combination thereof. Additional
exemplary causes for an alert are discussed below in the more
detailed discussion of the external assembly.
[0097] Typically, the alert is incorporated in the external
assembly 20 so that the external assembly can provide a visual,
audible, and/or tactile alert. Such an alert can indicate to the
subject (or third party) that the external assembly 20 is not able
to receive the RF signal from the implanted assembly 14 and/or that
appropriate data transfer is not occurring. Moreover, the alert may
reduce the likelihood of misplacing the external assembly 20, since
in most embodiments, once the data transfer is interrupted, the
alert may be activated by the system. In such a case, if the
subject were to walk away from the external assembly 20 (e.g.,
leave the external assembly 20 on a table), the subject would not
be advised of their susceptibility for seizure. If the subject did
not realize that they did not have their external assembly 20 with
them, the subject may assume that they are in a low susceptibility
and perform activities on the assumption that their external
assembly 20 would warn them of a changing to a state in which they
were in a higher susceptibility to a seizure.
[0098] Additionally or alternatively, it may be possible to
incorporate an alert in the implanted assembly 14 and the alert may
provide a tactile warning (e.g., vibration) and/or audible alert to
warn the subject that there is a data transmission error between
the external assembly 20 and the implanted assembly 14.
[0099] In some embodiments the external assembly can be adapted so
that it will expect to receive a data signal from the implanted
assembly, and if it does not, the alert will be activated. The
external assembly can be programmed to expect to receive a
substantially continuous data signal from the implanted assembly,
such that if the external assembly stops receiving a signal the
alert will be activated. The external assembly can also be
programmed to expect to receive a data signal periodically rather
than substantially continuously. For example, the external assembly
could expect to receive a signal every two seconds, and if it fails
to receive a signal after a two second period of time, the alert
will be activated. Thus, when the external assembly is adapted to
expect a data signal periodically, the alert will be activated
after a specified period of time passes without the external
assembly receiving the data signal.
[0100] In some embodiments the communication error comprises a gap
in the communication stream. For example, if the data signal
comprises a numbered sequence of packets of information, and the
external assembly receives a signal with missing packets of
information within the sequence, the alert would be activated. The
implanted assembly can be adapted to temporarily store the data
signal so that if the external assembly detects a gap in the
communication, the implanted assembly can attempt to retransmit the
complete data signal data.
[0101] In some embodiments the communication error can include data
formatting errors. An exemplary formatting error is an invalid
cyclic redundancy check, but formatting errors as described herein
include any other alteration of data during transmission or
storage.
[0102] FIG. 4 illustrates an exemplary method of activating an
alert when there is an error transmitting a data signal between the
implanted assembly and the external assembly. First, a brain
signal, such as an EEG signal, is sampled from the subject at step
55. The implanted assembly then attempts to transmit a data signal
which is indicative of the brain signal to the external assembly at
step 56. If there is a communication error between the implanted
assembly and the external assembly, step 57, the alert is
activated, step 58, to notify the subject of the communication
error. The implanted assembly can also attempt to retransmit the
data signal between the implanted assembly and the external
assembly if there is a communication error.
[0103] In some situations, the subject may be able to temporarily
disable the alert and/or change the mode or parameters of the alert
using a subject input. Such functionality may be carried out
through providing a manual subject input--such as pressing a button
on the external assembly 20.
[0104] In some embodiments, external assembly 20 may be programmed
to allow the subject to disable the alert if the subject is in one
or more different neurological states. For example, if the subject
is in a contra-ictal state in which the subject is at a low
susceptibility to transitioning into an ictal state and/or a
pro-ictal state in a period of time and did not want to carry the
external assembly 20 with them (e.g., to take a shower and leave
the external assembly 20 in the bedroom), the subject may disable
the alert by using the buttons 131, 133, 135 or other user inputs
on the external assembly 20 (FIG. 6). The disabling of the alert
could last for a predetermined time period and then automatically
be re-enabled, or the disabling of the alert may be continued until
the subject manually re-enables the alert.
[0105] The subject and/or the physician may also customize the
alert parameters to the subject. For example, some subjects may
want to be immediately alerted if there is a communication error,
while others may want a time delay before the alert is sounded.
[0106] Furthermore, if there is a prolonged alert (e.g., the
subject leaves the house without the external assembly), the
external assembly 20 may automatically disable the alert after a
predetermined time and/or the alert may be manually disabled by a
third party. To further reduce the likelihood of misplacing the
external assembly 20 and ensuring that the subject is being
monitored and advised, the external assembly 20 may comprise a
communication assembly that facilitates the wireless communication
with a remote party, such as the subject's caregiver, spouse, or
friend (described in more detail below as the caregiver advisory
device). Thus, if an alert is sounded that indicates a
communication error, the communication assembly may send a wireless
communication to the remote party to alert the third party that the
subject is not being advised of their susceptibility to seizure.
Typically, the wireless communication to the caregiver will be sent
only after a predetermined time period has elapsed.
[0107] Tuning or reprogramming of the components of implanted
assembly 14 may be carried out in vivo through communication
sub-assembly 46. For example, the external assembly 20 and/or a
dedicated programmer (controlled by physician) may be brought into
communication range with the communication sub-assembly 46 and the
reprogramming instructions may be uploaded into the processing
sub-assembly.
[0108] Communication sub-assembly may include a magnetic reed
switch (not shown) similar to those found in the Cyberonics.RTM.
Vagus Nerve Stimulator or spinal cord stimulators. The magnetic
reed switch would enable initiation of an electrode impedance
check, self test, RAM check, ROM check, power supply checks,
computer operating properly checks, electrode impedance check, or
the like.
[0109] Implantable assembly 14 can be configured to substantially
continuously sample the brain activity of the groups of neurons in
the immediate vicinity of each of the contacts in the electrode
array 12. The communication range between the implanted assembly 14
and the external assembly 20 is typically about 5 meters, but could
be as short as requiring that the external assembly 20 contact the
skin of the subject and up to 10 meters, or more. Sampling of the
brain activity is typically carried out at a sampling rate above
about 200 Hz, and preferably between about 200 Hz and about 1000
Hz, and most preferably between about 400 Hz and about 512 Hz, but
it could be higher or lower, depending on the specific condition
being monitored, the subject, and other factors. Each sample of the
subject's brain activity will typically contain between about 8
bits per sample and about 32 bits per sample, and preferably
between about 12 bits and 16 bits per sample. The wireless
communication link 18 may have an overall data transfer rate
between approximately 5 Kbits/sec and approximately 500 Kbits/sec,
and preferably about approximately 50 kbits/sec. As can be
appreciated, the over air data transfer rate of the implanted
assembly could be considerably higher (e.g., 2 Mbits/sec), which
would allow for a lower transmit duty cycle which will result in
power savings.
[0110] For example, if each communication transmission to the
external assembly includes one EEG sample per transmission, and the
sample rate is 400 Hz and there are 16 bits/sample, the data
transfer rate from the implantable assembly 14 to the external
assembly 20 is at least about 6.4 Kbits/second/channel. If there
are 16 channels, the total data transfer rate for the wireless
communication link 18 between the implanted assembly 14 and the
external assembly 20 would be about 102 Kbits/second.
[0111] While substantially continuous sampling and transmission of
brain activity is preferred, in alternative embodiments, it may be
desirable to have the implantable assembly 14 sample the brain
activity of the subject in a non-continuous basis or the sampling
rate may vary over the period of monitoring. In such embodiments,
the implantable assembly 14 may be configured to sample the brain
activity signals periodically (e.g., a burst of sampling every 5
seconds) or aperiodically. For example, it may be desirable to
reduce or increase the sampling rate when a subject has gone to
sleep.
[0112] To enable the high data transfer rates of the present
invention, the wireless communication link 18 provided by the
communication sub-assembly 46 is typically in the form of an
electromagnetic radiofrequency communication link. Conventional
devices typically use a slower communication link (e.g., that is
designed for low data transfer rates and long link access delays)
and transmit data out on a non-continuous basis. In contrast, the
present invention uses a fast access communication link that
transmits smaller bursts of data (e.g., single or small number of
EEG samples from each of the channels at a time) on a substantially
continuous basis so as to allow for substantially real-time
analysis of the EEG data. The radiofrequency used to transfer data
between the implantable assembly 14 and external assembly 20 is at
a frequency typically between 13.56 MHz and 10 GHz, preferably
between about 900 MHz and about 2.4 GHz, more preferably at about
2.4 GHz, or between about 900 MHz and about 928 MHz. One
potentially useful communication sub-assembly is a 900 MHz ISM
telemetry transmitter. If it is desired to avoid FCC regulations,
it may be desirable to use telemetry at low frequency, such as
below 9 KHz.
[0113] As can be appreciated, while the aforementioned frequencies
are the preferred frequencies, the present invention is not limited
to such frequencies and other frequencies that are higher and lower
may also be used. For example, it may be desirable us use the MICS
(Medical Implant Communication Service band) that is between
402-405 MHz to facilitate the communication link.
[0114] In order to facilitate data transmission from the implanted
assembly 14 to the external assembly 20, the antennas 47 and 62 of
the implantable assembly 14 and external assembly 14, respectively,
must be maintained in communication range of each other. The
frequency used for the wireless communication link has a direct
bearing on the communication range. Typically, the communication
range is typically at least one foot, preferably between about one
foot and about twenty feet, and more preferably between about six
feet and sixteen feet. As can be appreciated, however, the present
invention is not limited to such communication ranges, and larger
or smaller communication ranges may be used. For example, if an
inductive communication link is used, the communication range will
be smaller than the aforementioned range; but if higher frequencies
are used, the communication range may be larger than twenty
feet.
[0115] While not illustrated in FIGS. 1 to 4, the systems 10 of the
present invention may also make use of conventional or proprietary
forward error correction ("FEC") methods to control errors and
ensure the integrity of the data transmitted from the implantable
assembly 14 to the external assembly 20. Such forward error
correction methods may include such conventional implementations
such as cyclic redundancy check ("CRC"), checksums, or the
like.
[0116] In some situations, instead of a wireless link between the
implanted assembly 14 and the external assembly 20, it may be
desirable to have a wire running from the subject-worn data
collection assembly 20 to an interface (not shown) that could
directly link up to the implanted assembly 14 that is positioned
below the subject's skin. For example, the interface may take the
form of a magnetically attached transducer, as with cochlear
implants. This could enable higher rates of data transmission
between the implanted assembly 14 and the external assembly 20.
[0117] FIG. 5 illustrates a simplified embodiment of external
assembly 20. For example, in alternative embodiments the
functionality performed by a single sub-assembly shown in FIG. 5
may be embodied in multiple sub-assemblies, and/or the
functionality carried out by multiple sub-assemblies of FIG. 5 may
be combined into a single sub-assembly. Furthermore, other
embodiments of the external assembly 20 may have additional
functionalities not illustrated, while other embodiments may not
have all of the functionality and/or electronic components that are
illustrated in FIG. 5. External assembly 20 is typically portable
and comprises a housing 60 that is of a size that allows for
storage in a purse or pocket of the subject. The handheld housing
60 typically has a form factor of a MP3 player (e.g., Apple iPod),
cellular phone, personal digital assistant (PDA), pager, or the
like. In some embodiments, the components of the external assembly
20 may be integrated within a housing of such consumer electronics
devices.
[0118] FIGS. 6, 7, and 8 illustrate alternative embodiments of
external assembly 20.
[0119] The illustrated external assembly shows a user interface 72
that includes a variety of indicators for providing system status
and alerts to the subject. User interface 72 may include one or
more indicators 101 that indicate the subject's brain state. In the
illustrated embodiment, the output includes light indicators 101
(for example, LEDs) that comprise one or more (e.g., preferably two
or more) discrete outputs that differentiate between a variety of
different brain states. In the illustrated embodiment, the brain
state indicators 101 include a red light 103, yellow/blue light
105, and a green light 107 for indicating the subject's different
brain states (described more fully below). In some configurations
the lights may be solid, blink or provide different sequences of
flashing to indicate different brain states. If desired, the light
indicators may also include an "alert" or "information" light 109
that is separate from the brain state indicators so as to minimize
the potential confusion by the subject.
[0120] External assembly 20 may also include a liquid crystal
display ("LCD") 111 or other display for providing system status
outputs to the subject. The LCD 111 generally displays the system
components' status and prompts for the subject. For example, as
shown in FIG. 7, LCD 111 can display indicators, in the form of
text or icons, such as, for example, implantable device battery
strength 113, external assembly battery strength 115, and signal
strength 117 between the implantable device and the external
assembly 20. If desired, the LCD may also display the algorithm
output (e.g., brain state indication) and the user interface 72 may
not require the separate brain state indicator(s) 101. The output
on the LCD is preferably continuous, but in some embodiments may
appear only upon the occurrence of an event or change of the system
status and/or the LCD may enter a sleep mode until the subject
activates a user input. LCD 111 is also shown including a clock
119, audio status 121 (icon shows PAD is muted), and character
display 123 for visual text alerts to the subject--such as an
estimated time to seizure or an estimated "contra-ictal" time.
While not shown in FIG. 7, the LCD 111 may also indicate the amount
of free memory remaining on the memory card.
[0121] FIGS. 8.sub.a-8.sub.g illustrate a variety of different
views of another embodiment of the external assembly. FIGS. 8.sub.a
and 8.sub.b are two alternative top plan views of the external
assembly. FIGS. 8.sub.c and 8.sub.e are opposing side views. FIG.
8.sub.d is a back view. FIG. 8.sub.f is a front view. FIG. 8.sub.g
is a bottom view. The illustrated embodiment of FIG. 8 is a
pager-style external assembly that may be carried on a clip (not
shown) that may be used to couple the external assembly to the
subject's belt or bag. The typical dimensions of this embodiment of
the external assembly are typically
1.00''.times.2.50''.times.3.50'', but may be larger or smaller as
desired.
[0122] Similar to the other embodiments, the external assembly of
FIG. 8 comprises a plurality of user inputs 131, 133, 135, brain
state indicators 101 and outputs that indicate a state of the
system (e.g., LCD 111). As shown in FIG. 8.sub.b, the LCD may
comprise a plurality of different icons on the LCD 111 to indicate
the state of the system. For example, the illustrated embodiment
includes an external assembly battery indicator 115, implanted
device battery indicator 113, telemetry signal strength indicator
117, volume indicator 121, and a memory card status indicator 6. To
differentiate between the implanted device system state and
external assembly system state, it may be desirable to provide a
physical separation 7 between the icons. The physical separation
element 7 could be a physical barrier that overlays the LCD, two
separate LCDs that are spaced from each other, or simply a
discernable separation between icons on the LCD.
[0123] The LCD 111 and brain state indicators 101 are typically
viewable by the subject when it is attached to the subject's belt.
As such, the subject need only glance down onto the top surface of
the PAD when an audible or tactile indication is provided that
indicates a subject's brain state or change thereof.
[0124] In the embodiment of FIG. 8.sub.a, the brain state
indicators 103, 105, 107 may be positioned along the junction of
the top surface and front surface so as to be viewable from
multiple angles. In another embodiment shown in FIG. 8.sub.b,
either in addition to the brain state indicators 103, 105, 107 on
the front surface (FIG. 8.sub.f) or as an alternative to the brain
state indicator on the front surface, the top surface may have
brain state indicators 103', 105', 107' that are viewable from the
top surface. In the embodiment shown in 8.sub.b, the brain state
indicators 103', 105', 107' on the top surface may be different
colored and different shaped to further differentiate between the
different brain states. In both embodiments of FIGS. 8.sub.a and
8.sub.b the acknowledgement input 135 may be positioned along a top
surface of the external assembly so that the acknowledgement input
135 is readily accessible to the subject when the brain state
indicator 101 is activated.
[0125] The front surface of the external assembly may also comprise
a door 9 that houses the removable data card an on/off input button
(not shown). When opened, the subject may replace the full (or
defective) data card with a new card. Alternatively, if the subject
desires to turn on or off the external assembly, the subject may
activate the on/off input. Typically, the subject will keep the
external assembly on at all times, but in instances which require
the external assembly to be off (e.g., on an airplane), the subject
may have the ability to turn off the external assembly and stop the
transmission of the data signal from the implanted device--which
may help to conserve battery power of the external assembly and
implanted device.
[0126] Referring again to FIG. 6, external assembly 20 may also
include a speaker 125 and a pre-amp circuit to provide audio
outputs to the subject (e.g., beeps, tones, music, recorded voice
alerts, etc.) that may indicate brain state or system status to the
subject. User interface 72 may also include a vibratory output
device 127 and a vibration motor drive 129 to provide a tactile
alert to the subject, which may be used separately from or in
conjunction with the visual and audio outputs provided to the
subject. The vibratory output device 127 is generally disposed
within external assembly 20, and is described in more detail below.
Depending on the desired configuration any of the aforementioned
outputs may be combined to provide information to the subject.
[0127] The external assembly 20 preferably comprises one or more
subject inputs that allow the subject to provide inputs to the
external assembly. In the illustrated embodiment, the inputs
comprise one or more physical inputs (e.g., buttons 131, 133, 135)
and an audio input (in the form of a microphone 137 and a pre-amp
circuit).
[0128] Similar to conventional cellular phones, the inputs 131,
133, 135 may be used to toggle between the different types of
outputs provided by the external assembly. For example, the subject
can use buttons 133 to choose to be notified by tactile alerts such
as vibration rather than audio alerts (if, for example, a subject
is in a movie theater). Or the subject may wish to turn the alerts
off altogether (if, for example, the subject is going to sleep). In
addition to choosing the type of alert, the subject can choose the
characteristics of the type of alert. For example, the subject can
set the audio tone alerts to a low volume, medium volume, or to a
high volume.
[0129] Some embodiments of the external assembly 20 will allow for
recording audio, such as voice data. A dedicated voice recording
user input 131 may be activated to allow for voice recording. In
preferred embodiments, the voice recording may be used as an audio
subject seizure diary. Such a diary may be used by the subject to
record when a seizure has occurred, when an aura or prodrome has
occurred, when a medication has been taken, to record subject's
sleep state, stress level, etc. Such voice recordings may be time
stamped and stored in data storage of the external assembly and may
be transferred along with recorded EEG signals to the physician's
computer. Such voice recordings may thereafter be overlaid over the
EEG signals and used to interpret the subject's EEG signals and
improve the training of the subject's customized algorithm, if
desired.
[0130] The one or more inputs may also be used to acknowledge
system status alerts and/or brain state alerts. For example, if the
external assembly provides an output that indicates a change in
brain state, one or more of the LEDs 101 may blink, the vibratory
output may be produced, and/or an audio alert may be generated. In
order to turn off the audio alert, turn off the vibratory alert
and/or to stop the LEDs from blinking, the subject may be required
to acknowledge receiving the alert by actuating one of the user
inputs (e.g., button 135).
[0131] While the external assembly is shown having inputs 131, 133,
135, any number of inputs may be provided on the external assembly.
For example, in one alternate embodiment, the external assembly may
comprise only two input buttons. The first input button may be a
universal button that may be used to scroll through output mode
options. A second input button may be dedicated to voice recording.
When an alert is generated by the external assembly, either of the
two buttons may be used to acknowledge and deactivate the alert. In
other embodiments, however, there may be a dedicated user input for
acknowledging the alerts.
[0132] External assembly 20 may comprise a main processor 139 and a
complex programmable logic device (CPLD) 141 that control much of
the functionality of the external assembly. In the illustrated
configuration, the main processor and/or CPLD 141 control the
outputs displayed on the LCD 111, generates the control signals
delivered to the vibration device 127 and speaker 125, and receives
and processes the signals from buttons 131, 133, 135, microphone
137, and a real-time clock 149. The real-time clock 149 may
generate the timing signals that are used with the various
components of the system.
[0133] The main processor may also manage a data storage device
151, provides redundancy for a digital signal processor 143
("DSP"), and manage the telemetry circuit 147 and a charge circuit
153 for a power source, such as a battery 155.
[0134] While main processor 139 is illustrated as a single
processor, the main processor may comprise a plurality of separate
microprocessors, application specific integrated circuits (ASIC),
or the like. Furthermore, one or more of the microprocessors 139
may include multiple cores for concurrently processing a plurality
of data streams.
[0135] The CPLD 141 may act as a watchdog to the main processor 139
and the DSP 143 and may flash the LCD 111 and brain state
indicators 101 if an error is detected in the DSP 143 or main
processor 139. Finally, the CPLD 141 controls the reset lines for
the main microprocessor 139 and DSP 143.
[0136] A telemetry circuit 147 and antenna may be disposed in the
PAD 10 to facilitate one-way or two-way data communication with the
implanted device. The telemetry circuit 147 may be an off the shelf
circuit or a custom manufactured circuit. Data signals received
from the implanted device by the telemetry circuit 147 may
thereafter be transmitted to at least one of the DSP 143 and the
main processor 139 for further processing.
[0137] The DSP 143 and DRAM 145 receive the incoming data stream
from the telemetry circuit 147 and/or the incoming data stream from
the main processor 139. The brain state algorithms process the data
(for example, EEG data) and estimate the subject's brain state, and
are preferably executed by the DSP 143 in the PAD. In other
embodiments, however, the brain state algorithms may be implemented
in the implanted device, and the DSP may be used to generate the
communication to the subject based on the data signal from the
algorithms in the implanted device.
[0138] The main processor 139 is also in communication with the
data storage device 151. The data storage device 151 preferably has
at least about 7 GB of memory so as to be able to store data from
about 8 channels at a sampling rate of between about 200 Hz and
about 1000 Hz. With such parameters, it is estimated that the 7 GB
of memory will be able to store at least about 1 week of subject
data. Of course, as the parameters (e.g., number of channels,
sampling rate, etc.) of the data monitoring change, so will the
length of recording that may be achieved by the data storage device
151. Furthermore, as memory capacity increases, it is contemplated
that the data storage device will be larger (e.g., 10 GB or more,
20 GB or more, 50 GB or more, 100 GB or more, etc.). Examples of
some useful types of data storage device include a removable secure
digital card or a USB flash key, preferably with a secure data
format.
[0139] "Subject data" may include one or more of raw analog or
digital EEG signals, compressed and/or encrypted EEG signals or
other physiological signals, extracted features from the signals,
classification outputs from the algorithms, etc. The data storage
device 151 can be removed when full and read in card reader 157
associated with the subject's computer and/or the physician's
computer. If the data card is full, (1) the subsequent data may
overwrite the earliest stored data or (2) the subsequent data may
be processed by the DSP 143 to estimate the subject's brain state
(but not stored on the data card). While preferred embodiments of
the data storage device 151 are removable, other embodiments of the
data storage device may comprise a non-removable memory, such as
FLASH memory, a hard drive, a microdrive, or other conventional or
proprietary memory technology. Data retrieval off of such data
storage devices 151 may be carried out through conventional wired
or wireless transfer methods.
[0140] The power source used by the external assembly may comprise
any type of conventional or proprietary power source, such as a
non-rechargeable or rechargeable battery 155. If a rechargeable
battery is used, the battery is typically a medical grade battery
of chemistries such as a lithium polymer (LiPo), lithium ion
(Li-Ion), or the like. The rechargeable battery 155 will be used to
provide the power to the various components of the external
assembly through a power bus (not shown). The main processor 139
may be configured to control the charge circuit 153 that controls
recharging of the battery 155.
[0141] In addition to being able to communicate with the implanted
device, the external assembly may have the ability to communicate
wirelessly with a remote device--such as a server, database,
physician's computer, manufacturer's computer, or a caregiver
advisory device (all of which can be herein referred to as "CAD").
In the exemplary embodiment, the external assembly may comprise a
communication assembly (not shown) in communication with the main
processor 139 that facilitates the wireless communication with the
remote device. The communication assembly may be a conventional
component that is able to access a wireless cellular network, pager
network, wifi network, or the like, so as to be able to communicate
with the remote device. The wireless signal could be transfer of
data, an instant message, an email, a phone call, or the like.
[0142] In one particular embodiment, the external assembly is able
to deliver a signal through the communication assembly that is
received by the CAD so as to inform the caregiver of the subject's
brain state or change in brain state. The CAD would allow the
caregiver to be away from the subject (and give the subject
independence), while still allowing the caregiver to monitor the
subject's brain state and susceptibility for seizure. Thus, if the
subject's brain state indicates a high susceptibility for a seizure
or the occurrence of a seizure, the caregiver would be notified via
the CAD, and the caregiver could facilitate an appropriate
treatment to the subject (e.g., small dosage of an antiepileptic
drug, make the subject safe, etc.). A signal may be provided to the
caregiver only if the subject has a high susceptibility for a
seizure or if a seizure is detected, or it may provide the same
indications that are provided to the subject.
[0143] In yet other embodiments, the communication assembly could
be used to inform the caregiver that there is a communication error
between the subject's implanted assembly and external assembly, so
as to indicate that the subject is not being properly monitored and
advised. Such a communication would allow the caregiver to
intervene and/or inform the subject that they are not being
monitored.
[0144] In other embodiments, the communication assembly could be
used to facilitate either real-time or non-real time data transfer
to the remote server or database. If there is real time transfer of
data, such a configuration could allow for remote monitoring of the
subject's brain state and/or EEG signals. Non-real time transfer of
data could expedite transfer and analysis of the subject's recorded
EEG data, extracted features, or the like. Thus, instead of waiting
to upload the brain activity data from the subject's data storage
device, when the subject visits their physician, the physician may
have already had the opportunity to review and analyze the
subject's transferred brain activity data prior to the subject's
visit.
[0145] The external assembly may be configured to perform a self
hardware/software test to detect system errors--such as power
failures, software failures, impedance change, battery health of
the implanted device and external assembly, internal clock and
voltage reference, hardware (processors, memory, and firmware)
checks, or the like. The self test may be performed periodically,
upon initial startup, upon a system reset, or some combination
thereof. The system preferably runs a self-test on the external
assembly, implanted device, electrode array and the communication
links. The external assembly may emit a tone and/or display
information on the LCD at the initiation of the self-test(s). If
the external assembly, implanted device, electrode array and/or
communication link pass the self-test, the subject may be notified
with an alert indicating the respective devices passed the
self-test. If any of the components do not pass the self-test, the
subject can be alerted with an output that indicates which
component did not pass (for example, an icon on the LCD
representing the component which did not pass the test flashes).
There may also be an audio alert, such as a voice alert, that one
or some of the devices failed the test. The external assembly may
also indicate these failures with information or alert light 109
(FIG. 7). The system may then wait for input from the subject to
acknowledge the system failure(s) by depressing a button on the
external assembly (such as the "OK" button 135 in FIG. 6), which
indicates the user is aware of the alert. Additionally or
alternatively, there may be a text display on the LCD notifying the
subject to contact the manufacturer or physician to receive further
instructions.
[0146] The external assembly may be configured to be toggled
between two or more different modes of operation. In one
embodiment, the physician may toggle the external assembly between
three different modes of operations. Of course, it should be
appreciated that the external assembly may have as little as one
mode of operation, or more than three different modes of
operations.
[0147] In one example, a first mode of operation of the external
assembly may be merely data collection, in which data signals from
the implanted device are stored in the data storage 151 of the
external assembly. In such a mode, the user interface 72 may be
modified to only provide system status indications to the subject
via the LCD 111, and the brain state indicators 101 may be
temporarily disabled.
[0148] In a second mode of operation, after the brain state
algorithms have been trained on the subject's data that was
collected during the first mode of operation, the brain state
algorithms may be implemented to process substantially real-time
data signals and the brain state indicators 101 may be enabled so
as to inform the subject of their substantially real-time brain
state.
[0149] In a third mode of operation, it may be desirable to only
receive and process the data signals from the implanted device, but
no longer store the substantially continuous data signals in a
memory of the external assembly. For example, if the brain state
algorithms are performing as desired, the brain data signals from
the implanted device will not have to be stored and analyzed.
Consequently, the subject would not have to periodically replace
the data card as frequently. However, it may still be desirable to
store the data signals that immediately precede and follow any
detected seizure. Consequently, in the third mode such seizure data
signals may optionally be stored.
[0150] As noted above, in some embodiments the system comprises one
or more brain state algorithms. In one embodiment, the brain state
algorithms embodied in the present invention will generally
characterize the subject's brain state as either "Low
Susceptibility," "Unknown," "Elevated Susceptibility" or
"Detection." It is intended that these are meant to be exemplary
categories and are in no way to be limiting and additional brain
states or fewer brain state indicators may be provided. There may
be different types of algorithms which are configured to
characterize the brain state into more or less discrete states.
"Contra-ictal" generally means that brain activity indicates that
the subject has a low susceptibility to transition to an ictal
state and/or a pro-ictal state for an upcoming period of time (for
example, 60 minutes to 90 minutes). This is considered positive
information and no user lifestyle action is required. A pro-ictal
state generally means that the algorithm(s) in the PAD are
determining that the subject has an elevated susceptibility for a
seizure (possibly within a specified time period). A "detection"
state generally means that brain activity indicates that the
subject has already transitioned into an ictal state (e.g.,
occurrence of an electrographic seizure) or that there is an
imminent clinical seizure. User actions should be focused on safety
and comfort. An "unknown" state generally means the current type of
brain activity being monitored does not fit within the known
boundaries of the algorithms and/or that the brain activity does
not fit within the contra-ictal state, pro-ictal state, or ictal
state. Therefore no evaluation can be reliably made. "Unknown" can
also indicate there has been a change in the status of the brain
activity and while the subject does not have an elevated
susceptibility and no seizure has been detected, it is not possible
to reliable tell the subject that they may not transition into an
ictal state and/or pro-ictal state for a period of time. This state
is considered cautionary and requires some cautionary action such
as limiting exposure to risk. The two different types of "unknown"
may have separate brain state indicators, or they may be combined
into a single brain state indicator, or the user interface may not
provide the "unknown" state to the subject at all.
[0151] The external assembly preferably comprises visual
indicators, such as LEDs, notifying the subject of the determined
brain state. In one preferred embodiments, the visual indicators
for the brain state alerts will comprise a green, yellow/blue, and
red lights. The green light will be illuminated when the PAD
determines that the brain state is in a "low susceptibility to
seizure" state. The yellow or blue light will be illuminated when
the subject is in an "unknown" state. The PAD will emit a solid red
light when the subject is in the "high susceptibility" state. The
PAD will emit a blinking red light when the subject is in the
"detection" state. The light colors or number of light indicators
are not intended to be limiting. Any color may be used. It may be
desirable to include additional lights or colors (e.g., orange) to
further delineate the subject's estimated condition. In yet other
embodiments, it may be desirable to display only a green light and
red light.
[0152] Further exemplary details of external assembly 20 can be
found in U.S. Provisional Application No. 60/952,463, filed Jul.
27, 2007, the disclosure of which is incorporated by reference
herein in its entirety.
[0153] FIG. 9 illustrates an exemplary simplified method embodied
by the present invention. In use, the implantable assembly 14
samples the brain activity signals with the active contacts on the
electrode array 12 (step 80). The sampled brain activity signals
are transmitted to the implantable assembly 14 over leads 16 (but
this can also be done wirelessly). The implantable assembly 14 may
then pre-process the sampled brain activity signals as desired
(step 82), and then use the communication sub-assembly to transmit
a substantially continuous wireless RF signal to the external
assembly 20 that is encoded with EEG data (step 84). The RF signal
emitted by the internal assembly 14 is received by an antenna in
the external assembly, and the RF signal is decoded to extract the
EEG data (step 86). The sampled EEG data may thereafter be stored
in a memory of the external assembly 20 (step 88). Rather than
storing the data in a memory in the external assembly (step 88),
the data can also be transmitted to a remote device in substantial
real time without storage in the external assembly.
[0154] In preferred embodiments, the wireless signal is transmitted
substantially immediately after sampling of the EEG signal to allow
for substantially continuous real-time transfer of the subject's
EEG data to the external assembly 20. In alternate embodiments,
however, the RF signal with the encoded EEG data may be temporarily
buffered in an internal memory 52 (FIG. 4) of the implanted
assembly 14 and the communication transmission to the external
assembly 20 may be delayed by any desired time period and such
transmissions may include the buffered EEG data and/or a real-time
sampled EEG data.
[0155] Instead of sending large packets of stored data with each RF
communication transmission, the methods and devices of the present
invention substantially continuously sample physiological signals
from the subject and communicate in real-time small bits of data
during each RF signal communication to the external assembly. Of
course, for embodiments in which real-time data transfer is not
needed, it may be desirable to transmit larger packets of data to
the external assembly 20 using the communication link, and such a
communication protocol is also encompassed by the present
invention.
[0156] As noted above, the data signals that are wirelessly
transmitted from implanted assembly 14 may be encrypted so as to
help ensure the privacy of the subject's data prior to transmission
to the external assembly 20. Alternatively, the data signals may be
transmitted to the external assembly 20 with unencrypted EEG data,
and the EEG data may be encrypted prior to the storage of the EEG
data in the memory of external assembly 20 or prior to transfer of
the stored EEG data to the local computer workstation 22 or remote
server 26.
[0157] The download of brain activity data may be manually carried
out by the subject or automatically initiated by a component of
system 10. After a time period of collecting EEG data (e.g., one
day to one week, one week to two weeks, two weeks to one month,
etc.), the external assembly 20 may be manually put in
communication with a local computer workstation 22 through either a
wireless link or wired link to download the stored data to a memory
of the local computer workstation 22. For example, in one
embodiment, a wired USB 2.0 connection (improvements thereof or
other conventional interface) may be used to upload the stored EEG
data to the local computer workstation 22. Alternatively, instead
of downloading the data directly to a local or remote computer
workstation 22, 26, the data may be downloaded to a portable hard
drive or flash drive for temporary storage. In such embodiments,
the drive may thereafter be brought or delivered into the
physician's office for download and analysis.
[0158] Furthermore, as shown in FIG. 1, the communication
sub-assembly of external assembly 20 may have the capability to
continuously or periodically communicate wirelessly with a
broadband, high speed communication network 24--such as a cellular
network, pager network, the Internet (Wifi, WiMAX), or the like, to
automatically and wirelessly transmit the stored and/or real-time
data over the network 24 to a remote server (not shown) or remote
computer workstation 26.
[0159] For example, the local computer workstation 22 (or remote
computer workstation 26) may periodically command the external
assembly to upload the data from the memory of the external
assembly, or the external assembly may be programmed to
automatically upload the EEG data according to a predetermined
schedule or upon reaching a threshold level memory usage. By
incrementally downloading days or weeks of stored brain activity
data periodically, the subject's physician may be able to start
analysis of the brain activity data and possibly complete the
analysis of the long term data prior to the subject going to the
physician's office. If a subject were to bring in a week or month
of stored brain activity data for analysis by the physician, the
subject would have to wait hours, days or even weeks for the
analysis of the data to be completed. Consequently, instead of
waiting for the analysis, analysis of the data may be substantially
completed and therapy or diagnosis decisions may be made prior to
the office visit and the subject would be able to immediately
implement any changes or start therapy immediately after visiting
the office.
[0160] Once implanted in the subject, the systems 10 of the present
invention may be used for a variety of different data collection
and monitoring purposes. For example, in one usage the systems of
the present invention may be used to quantify seizure activity
statistics for the subject. Currently, the most common method of
quantifying a subject's seizure activity is through subject self
reporting using a seizure diary. However, it has been estimated
that up to 63% of all seizures are missed by subjects. Subject's
missing the seizures are usually caused by the subjects being
amnesic to the seizures, unaware of the seizures, mentally
incapacitated, the seizures occur during sleep, or the like. FIG.
10 illustrates a simplified method 90 of measuring a subject's
seizure activity statistics. At step 92, the electrode arrays 12,
leads 16 (or can be wireless), and implanted assembly 14 are
implanted in the subject. At step 94, the implanted assembly is
activated to substantially continuously sample EEG signals from the
subject. At step 96, the sampled EEG signals are wirelessly
transmitted from the implanted assembly 14 to an external assembly
20. At step 98, the sampled EEG signals are stored in a
memory--either in the external assembly 20 or in one of the
computer workstations 22, 26. At step 100, the stored EEG signals
are manually analyzed by the physician and/or analyzed with EEG
analysis software, typically using a seizure advisory algorithm(s)
or spike detector, to derive statistics for the clinical seizures
and/or the sub-clinical seizures for the subject based on the
long-term, ambulatory EEG data. For example, the following
statistics may be quantified using the present invention:
[0161] Seizure count over a time period--How many clinical and
sub-clinical seizures does the subject have in a specific time
period?
[0162] Seizure frequency--How frequent does the subject have
seizures? What is the seizure frequency without medication and with
medication? Without electrical stimulation and with electrical
stimulation?
[0163] Seizure duration--How long do the seizures last? Without
medication and with medication? Without electrical stimulation and
with electrical stimulation?
[0164] Seizure timing--When did the subject have the seizure? Do
the seizures occur more frequently at certain times of the day?
[0165] Seizure patterns--Is there a pattern to the subject's
seizures? After certain activities are performed? What activities
appear to trigger seizures for this particular subject?
[0166] Finally, at step 102, report generation software may be used
to generate a report based on the statistics for the seizure
activity. The report may include some or all of the statistics
described above, and may also include the EEG signal(s) associated
with one or more of the seizures. The report may include text,
graphs, charts, images, or a combination thereof so as to present
the information to the physician and/or subject in an actionable
format.
[0167] As noted above, the present invention enables the
quantification, documentation and long term monitoring of
sub-clinical seizures in a subject. Because the subject is unaware
of the occurrence of sub-clinical seizures, heretofore the long
term monitoring of sub-clinical seizures was not possible.
Documentation of the sub-clinical seizures may further provide
insight into the relationship between sub-clinical seizures and
clinical seizures, may provide important additional information
relevant to the effectiveness of subject therapy, and may further
enhance the development of additional treatments for epilepsy.
[0168] FIG. 11 illustrates one exemplary method of how the seizure
activity data may be used to evaluate the efficacy or clinical
benefit of a current or potential therapy and allow for the
intelligent selection of an appropriate therapy for an individual
subject or stopping the usage of ineffective therapies. Currently,
effectiveness of the AED therapy is based on self-reporting of the
subject, in which the subject makes entries in a diary regarding
the occurrence of their seizure(s). If the entries in the subject
diary indicate a reduction in seizure frequency, the AED is deemed
to be effective and the subject continues with some form of the
current regimen of AEDs. If the subject entries in the subject
diary do not indicate a change in seizure frequency, the AEDs are
deemed to be ineffective, and typically another AED is
prescribed--and most often in addition to the AED that was deemed
to be ineffective. Because AEDs are typically powerful neural
suppressants and are associated with undesirable side-effects, the
current methodology of assessing the efficacy of the AEDs often
keeps the subject on ineffective AEDs and exposes the subject to
unnecessary side-effects.
[0169] By way of example, a medically refractory subject coming to
an epilepsy center for the first time might first have the system
of the present invention implanted and then asked to collect data
for a prescribed time period, e.g., 30 days. The initial 30 days
could be used to establish a baseline measurement for future
reference. The physician could then prescribe an adjustment to the
subject's medications and have the subject collect data for another
time period, e.g., an additional 30 day period. Metrics from this
analysis could then be compared to the previous analysis to see if
the adjustment to the medications resulted in an improvement. If
the improvement was not satisfactory, the subject can be taken off
of the unsatisfactory medication, and a new medication could be
tried. This process could continue until a satisfactory level of
seizure control was achieved. The present invention provides a
metric that allows physicians and subjects to make informed
decisions on the effectiveness and non-effectiveness of the
medications.
[0170] FIG. 11 schematically illustrates this method 110. At step
114, the implantable assembly and external assembly are used to
monitor the subject's EEG to obtain a baseline measurement for the
subject. The baseline measurement is typically seizure activity
statistics for a specific time period (e.g., number of seizures,
seizure duration, seizure pattern, seizure frequency, etc.). It
should be appreciated however, that the baseline measurement may
include any number of types of metrics. For example, the baseline
metric may include univariate, bivariate, or multivariate features
that are extracted from the EEG, or the like. In one preferred
embodiment, the baseline measurement is performed while the subject
is not taking any AEDs or using any other therapy. In other
embodiments, however, the subject may be taking one or more AEDs
and the baseline measurement will be used to evaluate adjustments
to dosage or other add-on therapies.
[0171] At step 116, the therapy that is to be evaluated is
commenced. The therapy will typically be an AED and the subject
will typically have instructions from the neurologist,
epileptologist, or drug manufacturer regarding the treatment
regimen for the AED. The treatment regimen may be constant (e.g.,
one pill a day) throughout the evaluation period, or the treatment
regimen may call for varying of some parameter of the therapy
(e.g., three pills a day for the first week, two pills a day for
the second week, one pill a day for the third week, etc.) during
the evaluation period. During the evaluation period, the
implantable assembly and external assembly will be used to
substantially continuously sample the subject's EEG. The sampled
EEG may thereafter be processed to obtain a follow-up measurement
for the subject (Step 118). If the baseline measurement was seizure
statistics for the baseline time period, then the follow-up
measurement will be the corresponding seizure statistics for the
evaluation period. At step 120, the baseline measurement is
compared to the follow-up measurement to evaluate the therapy. If
the comparison indicates that the therapy did not significantly
change the subject's baseline, the therapy may be stopped, and
other therapies may be tried.
[0172] Currently, the primary metric in evaluating the efficacy of
an AED is whether or not the AED reduces the subject's seizure
count. In addition to seizure count, the systems of the present
invention would be able to track any reduction in seizure duration,
modification in seizure patterns, reduction in seizure frequency,
or the like. While seizure count is important, because the present
invention is able to provide much greater detail than just seizure
count, efficacy of an AED may be measured using a combination of
additional metrics, if desired. For example, if the subject was
having a large number of sub-clinical seizures, spike bursts, or
other epileptiform activity (which the subject was not aware of)
and the AED was effective in reducing or stopping the sub-clinical
seizures, the systems of the present invention would be able to
provide metrics for such a situation. With conventional subject
diary "metrics", the subject and physician would not be aware of
such a reduction, and such an AED would be determined to be
non-efficacious for the subject. However, because the present
invention is able to provide metrics for the sub-clinical seizures,
the efficacious medication could be continued.
[0173] At step 122, the epileptologist or neurologist may decide to
change one or more parameters of the therapy. For example, they may
change a dosage, frequency of dosage, form of the therapy or the
like, and thereafter repeat the follow-up analysis for the therapy
with the changed parameter. After the "second" follow up
measurement is complete, the second follow up data may be obtained
and thereafter compared to the "first" follow up measurements
and/or the baseline measurements.
[0174] Of course, the therapy is not limited to AED therapy.
Therapies that can be assessed by the present invention can include
cooling therapy, electrical stimulation (such as vagus nerve
stimulation, deep brain stimulation, cortical stimulation), or the
like. The present invention may be used to screen the subject's for
determining appropriate therapy for their condition and/or to
determine the appropriate parameters for the selected therapy.
[0175] In addition to evaluating an efficacy of a therapy for an
individual subject, the metrics that are provided by the present
invention also enable an intelligent titration of a subject's
medications. As shown in FIG. 12, if the subject is on a treatment
regimen of an efficacious therapy, the present invention may be
used to reduce/titrate a dosage or frequency of intake of the AED
(or AEDs) 130. Typically, the subject will already be on a
treatment regimen of the efficacious therapy, but if not, the
efficacious therapy is commenced with the prescribed parameters,
e.g., "standard" dosage (Step 134). At step 136, the subject's EEG
(and/or other physiological signal) is monitored for a desired time
period to obtain a first subject data measurement for the subject
(e.g., the baseline measurement). Similar to previous embodiments,
the first subject data measurement may be any desired metrics, but
will typically be selected from clinical seizure frequency,
clinical seizure duration, sub-clinical seizure frequency,
sub-clinical seizure duration, medication side effects. At step
138, after the baseline measurement has been taken, the first
efficacious therapy is stopped and a therapy with at least one
changed parameter is started (referred to as "therapy with second
parameters" in FIG. 12). Typically, the changed parameter will be a
reduction in dosage, but it could be changing a frequency of the
same dosage, a change in formulation or form of the same AED, or
the like.
[0176] At step 140, the subject's EEG is monitored and processed to
obtain a second subject data measurement for the subject (e.g.,
follow-up data measurement). If the neurologist or epileptologist
is satisfied with the results, the titration may end. But in many
embodiments, the titration process will require more than one
modification of parameters of the therapy. In such embodiments, the
second therapy is stopped (step 142), and a therapy with N.sup.th
parameters (e.g., third, fourth, fifth . . . ) is commenced (step
144). Monitoring and processing of the subject's EEG signals are
repeated (step 146), and the process is repeated a desired number
of times (as illustrated by arrow 147). Once the desired numbers of
modifications to the therapy have been made, the various subject
data measurements may be analyzed and compared to each other to
determine the most desirous parameters for the therapy (step
148).
[0177] With the instrumentation provided by the present invention,
the process of selecting appropriate AEDs and the dosages of such
AEDs could occur much faster and with much greater insight than
ever before. Further, the chance of a subject remaining on an
incremental AED that was providing little incremental benefit would
be minimized. Once a subject was under control, the subject could
cease the use of the system, but the implantable assembly could
remain. In the future, the subject might be asked to use the system
again should their condition change.
[0178] In addition to or as an alternative to the above data
collection uses, the systems 10 of the present invention may be
used to analyze EEG data substantially in real-time and provide an
output to the subject and/or provide a therapy to the subject based
on the analysis of the EEG data. In preferred embodiments, the
systems of the present invention may be used as seizure advisory
systems that measure the subject's susceptibility to a seizure
and/or to detect the onset of the seizure prior to the clinical
manifestation of the seizure and provide an appropriate warning to
the subject.
[0179] The platform of system 10 used for data collection
(described above) and the system used for determining the subject's
susceptibility for having a seizure will generally have the same
general components, so that the same system may be used for both
data collection and advising of susceptibility to seizure. However,
when the system is used for data collection during a training
period, the algorithms that determine the subject's susceptibility
of having a seizure may be disabled or not yet programmed in the
system so as to not be accessible to the subject. If and when
seizure advising is desired, such algorithms may be enabled and/or
added into the system.
[0180] For example, EEG data may be collected as noted above. The
collected EEG data may be analyzed off-line (e.g., in a separate
computer, such as workstation 22) and, if desired, algorithms may
be customized or otherwise tuned to the subject specific EEG data.
Thereafter, the parameters of the disabled algorithm(s) may be
modified or the entire tuned algorithm may be uploaded to a memory
of system 10 and the aspects of the system relevant to seizure
advising may be enabled. Finally, the seizure advising
functionality in the system 10 may be enabled and used by the
subject in real-time on a substantially continuous basis.
[0181] FIG. 13 illustrates an embodiment of the seizure advisory
system in which the electrode array 12 includes at least one depth
electrode array, but otherwise contains similar components as the
system of FIG. 1. Typically, the depth electrode will be only for
sampling EEG signals, but as will be described below, the electrode
arrays 12 may be used to deliver electrical stimulation directly to
the brain. The system 10 shown in FIGS. 1 and 13 will include
algorithms that process the EEG in substantially real-time to
determine the subject's susceptibility for having a seizure. When a
high susceptibility to a seizure is determined, a user interface of
the external assembly 20 will provide an output to the subject that
is indicative of the high susceptibility to the seizure. In the
illustrated embodiment, the output to the subject may be a visual
display on the LCD, a light display on the LED, a vibratory signal,
and/or an audio output, etc., as described above.
[0182] FIG. 14 depicts an example of the overall structure of a
system for performing substantially real-time assessment of the
subject's brain activity and for determining the communication
output that is provided to the subject. The system may comprise one
or more algorithms or modules that process input data 162. The
algorithms may take a variety of different forms, but typically
comprises one or more feature extractors 164a, 164b, 165 and at
least one classifier 166 and 167. The embodiment illustrated in
FIG. 14 shows a contra-ictal algorithm 163 and a pro-ictal
algorithm 161 which share at least some of the same feature
extractors 164a and 164b. In alternative embodiments, however, the
algorithms used in the system may use exactly the same feature
extractors or completely different feature extractors.
[0183] The input data 162 is typically EEG, but may comprise
representations of physiological signals obtained from monitoring a
subject and may comprise any one or combination of the
aforementioned physiological signals from the subject. The input
data may be in the form of analog signal data or digital signal
data that has been converted by way of an analog to digital
converter (not shown). The signals may also be amplified,
preprocessed, and/or conditioned to filter out spurious signals or
noise. For purposes of simplicity the input data of all of the
preceding forms is referred to herein as input data 162. In one
preferred embodiment, the input data comprises between about 1
channel and about 64 channels of EEG from the subject.
[0184] The input data 162 from the selected physiological signals
is supplied to the one or more feature extractors 164a, 164b, 165.
Feature extractor 164a, 164b, 165 may be, for example, a set of
computer executable instructions stored on a computer readable
medium, or a corresponding instantiated object or process that
executes on a computing device. Certain feature extractors may also
be implemented as programmable logic or as circuitry. In general,
feature extractors 164a, 164b, 165 can process data 162 and
identify some characteristic of interest in the data 162. Such a
characteristic of the data is referred to herein as an extracted
feature.
[0185] Each feature extractor 164a, 164b, 165 may be univariate
(operating on a single input data channel), bivariate (operating on
two data channels), or multivariate (operating on multiple data
channels). Some examples of potentially useful characteristics to
extract from signals for use in determining the subject's
propensity for a neurological event, include but are not limited
to, bandwidth limited power (alpha band [8-13 Hz], beta band [13-18
Hz], delta band [0.1-4 Hz], theta band [4-8 Hz], low beta band
[12-15 Hz], mid-beta band [15-18 Hz], high beta band [18-30 Hz],
gamma band [30-48 Hz], high frequency power [>48 Hz], bands with
octave or half-octave spacings, wavelets, etc.), second, third and
fourth (and higher) statistical moments of the EEG amplitudes or
other features, spectral edge frequency, decorrelation time, Hjorth
mobility (HM), Hjorth complexity (HC), the largest Lyapunov
exponent L(max), effective correlation dimension, local flow,
entropy, loss of recurrence LR as a measure of non-stationarity,
mean phase coherence, conditional probability, brain dynamics
(synchronization or desynchronization of neural activity, STLmax,
T-index, angular frequency, and entropy), line length calculations,
first, second and higher derivatives of amplitude or other
features, integrals, and mathematical linear and non-linear
operations including but not limited to addition, subtraction,
division, multiplication and logarithmic operations. Of course, for
other neurological conditions, additional or alternative
characteristic extractors may be used with the systems described
herein.
[0186] The extracted characteristics can be supplied to the one or
more classifiers 166, 167. Like the feature extractors 164a, 164b,
165, each classifier 166, 167 may be, for example, a set of
computer executable instructions stored on a computer readable
medium or a corresponding instantiated object or process that
executes on a computing device. Certain classifiers may also be
implemented as programmable logic or as circuitry.
[0187] The classifiers 166, 167 analyze one or more of the
extracted characteristics, and either alone or in combination with
each other (and possibly other subject dependent parameters),
provide a result 168 that may characterize, for example, a
subject's condition. The output from the classifiers may then be
used to determine the subject's susceptibility for having a
seizure, which can determine the output communication that is
provided to the subject regarding their condition. As described
above, the classifiers 166, 167 are trained by exposing them to
training measurement vectors, typically using supervised methods
for known classes, e.g. ictal, and unsupervised methods as
described above for classes that can't be identified a priori, e.g.
contra-ictal. Some examples of classifiers include k-nearest
neighbor ("KNN"), linear or non-linear regression, Bayesian,
mixture models based on Gaussians or other basis functions, neural
networks, and support vector machines ("SVM"). Each classifier 166,
167 may provide a variety of output results, such as a logical
result or a weighted result. The classifiers 166, 167 may be
customized for the individual subject and may be adapted to use
only a subset of the characteristics that are most useful for the
specific subject. Additionally, over time, the classifiers 166, 167
may be further adapted to the subject, based, for example, in part
on the result of previous analyses and may reselect extracted
characteristics that are used for the specific subject.
[0188] For the embodiment of FIG. 14, the pro-ictal classifier 167
may classify the outputs from feature extractors 164a, 164b to
detect characteristics that indicate that the subject is at an
elevated susceptibility for a neurological event, while the
contra-ictal classifier 166 may classify the outputs from feature
extractors 164a, 164b, 165 to detect characteristics that occur
when the subject is unlikely to transition into an ictal condition
for a specified period of time. The combined output of the
classifiers 166, 167 may be used to determine the output
communication provided to the subject. In embodiments which
comprise only the contra-ictal algorithm, the output from the
contra-ictal classifier 166 alone may be used to determine the
output communication to the subject. Further details of exemplary
algorithms that may be used to identify a subject's susceptibility
to having a seizure may be found in U.S. Provisional Patent
Application No. 60/897,549, filed Jan. 25, 2007, to Snyder et al.,
entitled "Systems and Methods for Identifying a Contra-ictal
Condition in a Subject" and co-pending Application No. 12/020,450,
filed on Jan. 25, 2008, titled "Systems and Methods for Identifying
a Contra-Ictal Condition in a Subject", the complete disclosures of
which are incorporated herein by reference.
[0189] Depending on the specific feature extractors and classifiers
used, the computational demands of the analysis provided by feature
extractors 164a, 164b, 165 and classification provided by
classifiers 166, 167 can be extensive. In the case of ambulatory
systems supplied by portable power sources, such as batteries,
supplying the power required to meet the computational demands can
severely limit power source life. In preferred embodiments, both
the seizure advisory algorithm are embodied in the external
assembly 20. Processing the EEG data with the algorithms in the
external assembly 20 provides a number of advantages over having
the algorithms in the implanted assembly. First, keeping the
processing in the external assembly 20 will reduce the overall
power consumption in the implanted assembly 14 and will prolong the
battery life of the implanted assembly 14. Second, charging of
battery or replacing the battery of the external assembly 20 is
much easier to accomplish. The battery of the external assembly may
be charged by placing the external assembly 20 in a recharging
cradle (e.g., inductive recharging) or simply by attaching the
external assembly to an AC power source. Third, customizing, tuning
and/or upgrading the algorithms will be easier to achieve in the
external assembly 20. Such changes may be carried out by simply
connecting the external assembly to the physician's computer
workstation 20 and downloading the changes. Alternatively,
upgrading may be performed automatically over a wireless connection
with the communication sub-assembly 64.
[0190] While it is preferred to have the observer algorithms 160 in
the external assembly 20, in alternate embodiments of the present
invention, the observer algorithms 160 may be wholly embodied in
the implanted assembly 14 or a portion of one or more of the
observer algorithms 160 may be embodied in the implanted assembly
14 and another portion of the one or more algorithms may be
embodied in the external assembly 20. In such embodiments, the
processing sub-assembly 44 (or equivalent component) of the
implanted assembly 14 may execute the analysis software, such as a
seizure advisory algorithm(s) or portions of such algorithms. For
example, in some configurations, one or more cores of the
processing sub-assembly 44 may run one or more feature extractors
that extract features from the EEG signal that are indicative of
the subject's susceptibility to a seizure, while the classifier
could run on a separate core of the processing sub-assembly 44.
Once the feature(s) are extracted, the extracted feature(s) may be
sent to the communication sub-assembly 46 for the wireless
transmission to the external assembly 20 and/or store the extracted
feature(s) in memory sub-system 52 of the implanted assembly 14.
Because the transmission of the extracted features is likely to
include less data than the EEG signal itself, such a configuration
will likely reduce the bandwidth requirements for the wireless
communication link 18 between the implantable assembly 14 and the
external assembly 20.
[0191] In other embodiments, the seizure advisory algorithms may be
wholly embodied within the implanted assembly 14 and the data
transmission to the external assembly 29 may include the data
output from the classifier, a warning signal, recommendation, or
the like. A detailed discussion of various embodiments of the
internal/external placement of such algorithms are described in
commonly owned U.S. patent application Ser. No. 11/322,150, filed
Dec. 28, 2005 to Bland et al., and U.S. Provisional Patent
Application 60/805,710, filed Jun. 23, 2006, the complete
disclosures of which are incorporated herein by reference.
[0192] FIG. 15 illustrates a method of using the systems described
herein to collect data, tune the algorithms and use the tuned
algorithms to estimate the subject's susceptibility to a seizure.
At step 200, the subject is implanted with the system 10 in which
the seizure advisory algorithms are disabled or not yet present in
the system. The user interface aspects that are related to the
seizure advising may also be disabled.
[0193] At step 202, the system is used to collect EEG data for a
desired time period, as described in detail above. Generally, the
desired time period will be a specified time period such as at
least one week, between one week and two weeks, between two weeks
and one month, between one month and two months, or two months or
more. But the desired time period may simply be a minimum time
period that provides a desired number of seizure events. At step
204, the collected EEG data may be periodically downloaded to the
physician's computer workstation or the entire EEG data may be
brought into the physician's office in a single visit.
[0194] At step 206, the physician may analyze the EEG data using
the computer workstation that is running EEG analysis software, the
EEG data may be transferred to a remote analyzing facility that
comprises a multiplicity of computing nodes where the EEG data may
be analyzed on an expedited basis, or it may even be possible to
analyze the EEG analysis software in the external assembly 20.
Analysis of the EEG data may be performed in a piecewise fashion
after the shorter epochs of EEG data is uploaded to the database,
or the analysis of the EEG data may be started after the EEG data
for the entire desired time period has been collected. Typically,
"analysis of the EEG data" will include identifying and annotating
at least some of spike bursts, the earliest electrographic change
(EEC), unequivocal electrical onset (UEO), unequivocal clinical
onset (UCO), electrographic end of seizure (EES). Identification of
such events may be performed automatically with a seizure detection
algorithm, manually by board-certified epileptologists, or a
combination thereof. After the EEG data is annotated, the seizure
advisory algorithm(s) may be trained on the annotated EEG data in
order to tune the parameters of the algorithm(s) to the subject
specific EEG data.
[0195] Once the algorithm(s) are tuned to meet minimum performance
criteria, at step 208 the tuned algorithm(s) or the parameter
changes to the base algorithm may be uploaded to the external
assembly 20. At step 210, the tuned algorithm and the other user
interface aspects of the present invention may be activated, and
the observer algorithm may be used by the subject to monitor the
subject's susceptibility to a seizure and/or detect seizures.
[0196] When the seizure advisory system 10 determines that the
subject is at an increased susceptibility to a seizure (or
otherwise detects a seizure), the external assembly may be
configured to generate a seizure warning to the subject, as
described above. For example, the external assembly may activate a
red or yellow LED light, generate a visual warning on the LCD,
provide an audio warning, deliver a tactile warning, or any
combination thereof. If desired, the warning may be "graded" so as
to indicate the confidence level of the seizure advisory, indicate
the estimated time horizon until the seizure, or the like.
"Grading" of the warning may be through generation of different
lights, audio, or tactile warning or a different pattern of lights,
audio or tactile warnings.
[0197] Additionally or alternatively, the external assembly may
include an instruction to the subject regarding an appropriate
therapy for preventing or reducing the susceptibility for the
seizure. The instruction may instruct the subject to take a dosage
of their prescribed AED, perform biofeedback to prevent/abort the
seizure, manually activate an electrical stimulator (e.g., use a
wand to activate an implanted VNS device) or merely to instruct the
subject to make themselves safe. A more complete description of
various instructions that may be output to the subject are
described in commonly owned, copending U.S. patent application Ser.
Nos. 11/321,897 and 11/321,898, both of which are incorporated by
reference herein.
[0198] The outputs provided to the subject via the external
assembly may be a standardized warning or instruction, or it may be
programmed by the physician to be customized specifically to the
subject and their condition. For example, different subjects will
be taking different AEDs, different dosages of the AEDs, and some
may be implanted with manually actuatable stimulators (e.g.,
NeuroPace RNS, Cyberonics VNS, etc.), and the physician will likely
be desirous to customize the therapy to the subject. Thus, the
physician will be able to program the warning and/or instruction to
correspond to the level of susceptibility, estimated time horizon
to seizure, or the like.
[0199] The systems 10 of the present invention may also be adapted
to provide closed-loop therapy to the subject. FIG. 16 illustrates
one embodiment of the system 10 that includes therapy delivery
assembly in the implanted assembly 14. The system 10 illustrated in
FIG. 16 will generally have the same components as shown in FIGS. 1
and 13, but will also include an implanted pulse generator (not
shown) that is in communication with a vagus nerve cuff electrode
220 via a lead 222. When the seizure advisory system determines
that the subject is at an elevated susceptibility to a seizure, the
system may automatically initiate delivery of electrical
stimulation to the vagus nerve cuff electrode. The parameters
(e.g., burst/no burst mode, amplitude, pulse width, pulse
frequency, etc.) of the electrical stimulation may be varied based
on the subject's susceptibility, or the parameter may be
constant.
[0200] While not shown in FIG. 16, the present invention further
embodies other therapy outputs--such as electrical stimulation of
the brain tissue (e.g., deep brain structures, cortical
stimulation) using electrode array 12 or other electrode arrays
(not shown), stimulation of cranial nerves (e.g., trigeminal
stimulation), delivery of one or more drugs via implanted drug
dispensers, cryogenic therapy to the brain tissue, cranial nerves,
and/or peripheral nerves), or the like. Similar to vagus nerve
stimulation, parameters of the therapy may be constant or the
parameters of the therapy may be modified based on the subject's
estimated susceptibility.
[0201] Such therapies may be used in addition to the vagus nerve
stimulation or as an alternative to such therapy. If desired, the
type of therapy delivered to the subject may be modified based on
the subject's susceptibility. For example, if the elevated
susceptibility estimates a long time horizon until seizure and/or a
lower confidence level, a more benign type of therapy (e.g.,
electrical stimulation) may be employed. But if the elevated
susceptibility estimates a shorter time horizon until seizure
and/or has a higher confidence level, a different type of therapy
(e.g., pharmacotherapy) may be employed.
[0202] FIG. 17 illustrates an embodiment of the present invention
that is used with an existing open loop Cyberonics vagus nerve
stimulator 300. When the system 10 of the present invention
determines that the subject is at an elevated risk for a seizure,
the system 10 may generate a communication to the subject via the
external assembly 20, and the subject may use a wand associated
with the vagus nerve stimulator 300 to manually active stimulation
of the vagus nerve.
[0203] Some embodiments of the monitoring system may include an
integral subject diary functionality. The subject diary may be a
module in the external assembly and inputs by the subject may be
used to provide secondary inputs to provide background information
for the sampled EEG signals. For example, if a seizure is recorded,
the seizure diary may provide insight regarding a trigger to the
seizure, or the like. The diary may automatically record the time
and date of the entry by the subject. Entries by the subject may be
a voice recording, or through activation of user inputs on the
external assembly. The diary may be used to indicate the occurrence
of an aura, occurrence of a seizure, the consumption of a meal,
missed meal, delayed meal, activities being performed, consumption
of alcohol, the subject's sleep state (drowsy, going to sleep,
waking up, etc.), mental state (e.g., depressed, excited,
stressed), intake of their AEDs, medication changes, missed dosage
of medication, menstrual cycle, illness, or the like. Thereafter,
the subject inputs recorded in the diary may also be used by the
physician in assessing the subject's epilepsy state and/or
determine the efficacy of the current treatment. Furthermore, the
physician may be able to compare the number of seizures logged by
the subject to the number of seizures detected by the seizure
detection algorithm.
[0204] While preferred embodiments of the present invention have
been shown and described herein, it will be obvious to those
skilled in the art that such embodiments are provided by way of
example only. Numerous variations, changes, and substitutions will
now occur to those skilled in the art without departing from the
invention. It should be understood that various alternatives to the
embodiments of the invention described herein may be employed in
practicing the invention. For example, the present invention also
encompasses other more invasive embodiments which may be used to
monitor the subject's neurological system. It is intended that the
following claims define the scope of the invention and that methods
and structures within the scope of these claims and their
equivalents be covered thereby.
* * * * *