U.S. patent application number 16/752382 was filed with the patent office on 2020-09-10 for system and method for improved obstructive sleep apnea diagnostic for implantable devices.
The applicant listed for this patent is Medtronic Xomed, LLC. Invention is credited to Patrick W. Kinzie, Avram Scheiner, Randal Schulhauser.
Application Number | 20200281522 16/752382 |
Document ID | / |
Family ID | 1000004641390 |
Filed Date | 2020-09-10 |
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United States Patent
Application |
20200281522 |
Kind Code |
A1 |
Scheiner; Avram ; et
al. |
September 10, 2020 |
SYSTEM AND METHOD FOR IMPROVED OBSTRUCTIVE SLEEP APNEA DIAGNOSTIC
FOR IMPLANTABLE DEVICES
Abstract
A system and method of diagnosing sleep apnea including an
implantable device with a sensor, a telemetry circuit and a memory,
an external programmer in communication with the telemetry circuit
and configured to receive data collected by the sensor and stored
in the memory. The system and method include operation of a server,
including a processor, in communication with the external
programmer and storing an application including instructions that
when executed by the processor executes steps of receiving the data
collected by the sensor from the external programmer, analyzing the
received data collected by the sensor, and transmitting to a remote
computer an assessment of the received sensor data, wherein the
assessment includes an evaluation of sleep apnea for the
patient.
Inventors: |
Scheiner; Avram; (Vadnais
Heights, MN) ; Kinzie; Patrick W.; (Glendale, AZ)
; Schulhauser; Randal; (Phoenix, AZ) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Medtronic Xomed, LLC |
Jacksonville |
FL |
US |
|
|
Family ID: |
1000004641390 |
Appl. No.: |
16/752382 |
Filed: |
January 24, 2020 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
62814398 |
Mar 6, 2019 |
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61B 5/0031 20130101;
A61B 2562/0219 20130101; A61B 5/0015 20130101; A61B 5/7264
20130101; A61B 5/0004 20130101; A61B 5/4818 20130101 |
International
Class: |
A61B 5/00 20060101
A61B005/00 |
Claims
1. A method of assessing a patient for sleep apnea comprising:
receiving sensor data from a device implanted in a patient for
treatment of a heart related disease at an external programmer;
transmitting the received sensor data to a remote server; analyzing
the received data at the server; and transmitting to a remote
computer an assessment of the received sensor data, wherein the
assessment includes an evaluation of sleep apnea for the
patient.
2. The method of claim 1, further comprising receiving sensor data
from an external sensor.
3. The method of claim 1, further comprising receiving
self-reported data.
4. The method of claim 1, wherein the sensor data includes data
indicative of the posture of the patient, motion data of the
patient, electroencephalogram (EEG) data, electrocardiogram (ECG)
data, Apnea Hypopnea Index (AHI) data or blood-oxygen saturation
data.
5. The method of claim 1, wherein the sensor data includes data
from one or more three-axis accelerometers.
6. The method of claim 1, wherein the sensor data includes
respiration rate data, heart rate data, total sleep time data,
sleep efficiency data, sleep stage data, arousals data, or
awakenings data.
7. The method of claim 1, wherein the implanted device selected
from the group consisting of a pacemaker, an implantable cardiac
defibrillators (ICD), a cardiac resynchronization therapy (CRT)
device, and an implantable neurostimulator (INS).
8. The method of claim 1, further comprising a neural network
performing the analysis of the received data.
9. A system comprising: an implantable device including a sensor, a
telemetry circuit and a memory; an external programmer in
communication with the telemetry circuit and configured to receive
data collected by the sensor and stored in the memory; a server,
including a processor, in communication with the external
programmer and storing thereon an application including
instructions that when executed by the processor executes steps of:
receiving the data collected by the sensor from the external
programmer; and analyzing the received data collected by the
sensor; and transmitting to a remote computer an assessment of the
received sensor data, wherein the assessment includes an evaluation
of sleep apnea for patient in which the implantable device has been
implanted.
10. The system of claim 8, further comprising one or more external
sensors configured to transmit sensor data to the server or the
external programmer.
11. The system of claim 8, further comprising a user-interface
presented on the external programmer and configured to receive
self-reported data.
12. The system of claim 8, wherein the sensor outputs data
indicative of the posture of the patient, motion of the patient, an
electroencephalogram (EEG), an electrocardiogram (ECG), an Apnea
Hypopnea Index (AHI) or blood-oxygen saturation.
13. The system of claim 8, wherein the sensor is comprised of one
or more three-axis accelerometers.
14. The system of claim 8, wherein the sensor outputs data
indicative of respiration rate, heart rate, total sleep time, sleep
efficiency, sleep stage, arousals, or awakenings.
15. The system of claim 8, wherein the implanted device selected
from the group consisting of a pacemaker, an implantable cardiac
defibrillators (ICD), a cardiac resynchronization therapy (CRT)
device, and an implantable neurostimulator (INS).
16. The system of claim 8, further comprising a neural network
performing the analysis of the received data at the server.
17. A computer readable recording medium storing thereon
instructions that when executed by a processor and cause the
processor to execute the steps of: receiving sensor data from an
external processor, the sensor data having been collected by an
implanted device configured for treatment of a heart related
disease; analyzing the received sensor data; and transmitting to a
remote computer an assessment of the received sensor data, wherein
the assessment includes an evaluation of sleep apnea for a patient
in which the implantable device has been implanted.
18. The computer readable recording medium of claim 17, wherein the
sensor data includes data indicative of the posture of the patient,
motion data of the patient, electroencephalogram (EEG) data,
electrocardiogram (ECG) data, Apnea Hypopnea Index (AHI) data or
blood-oxygen saturation data.
19. The computer readable recording medium of claim 17, wherein the
sensor data includes data from one or more three-axis
accelerometers.
20. The computer readable recording medium of claim 17, wherein the
sensor data includes respiration rate data, heart rate data, total
sleep time data, sleep efficiency data, sleep stage data, arousals
data, or awakenings data.
Description
CROSS-REFERENCE TO RELATED APPLICATION
[0001] This application claims priority to U.S. Provisional
Application No. 62/814,398 filed Mar. 6, 2019 and entitled
INTRAMUSCULAR HYPOGLOSSAL NERVE STIMULATION FOR OBSTRUCTIVE SLEEP
APNEA THERAPY, the entire contents of which are incorporated herein
by reference.
TECHNICAL FIELD
[0002] This disclosure relates to implantable medical device
systems and methods of assessing physiological data to diagnose
sleep apnea.
BACKGROUND
[0003] Implantable medical devices capable of delivering electrical
stimulation pulses have been proposed or are available for treating
a variety of medical conditions, such as cardiac arrhythmias and
chronic pain as examples. Sleep apnea is generally separated into
two forms obstructive sleep apnea (OSA) and central sleep apnea
(CSA). Sleep apnea is a serious disorder in which breathing is
irregularly and repeatedly stopped and started during sleep,
resulting in disrupted sleep and reducing blood oxygen levels. OSA
is caused by complete or partial collapse of the pharynx during
sleep. In particular, muscles in a patient's mouth and throat
intermittently relax thereby obstructing the upper airway while
sleeping. Airflow into the upper airway can be obstructed by the
tongue or soft pallet moving to the back of the throat and covering
a smaller than normal airway. Loss of air flow also causes unusual
inter-thoracic pressure as a person tries to breathe with a blocked
airway. In contrast CSA is generally the result of the cessation of
respiratory drive. That is, the brain fails to provide the
necessary signals to your diaphragm and other muscles to engage in
breathing. Regardless in both OSA and CSA Lack of adequate levels
of oxygen during sleep can contribute to abnormal heart rhythms,
heart attack, heart failure, high blood pressure, stroke, memory
problems and increased accidents. Indeed, sleep apnea has a high
rate of co-morbidity with many forms of heart disease and
particularly cardiac rhythm disease. Additionally, loss of sleep
occurs when a person is awakened during an apneic episode.
SUMMARY
[0004] One aspect of the disclosure is directed to a method of
assessing a patient for sleep apnea including: receiving sensor
data from a device implanted in a patient for treatment of a heart
related disease at an external programmer; transmitting the
received sensor data to a remote server; analyzing the received
data at the server; and transmitting to a remote computer an
assessment of the received sensor data, where the assessment
includes an evaluation of sleep apnea for the patient. Other
embodiments of this aspect include corresponding computer systems,
apparatus, and computer programs recorded on one or more computer
storage devices, each configured to perform the actions of the
methods and systems described herein.
[0005] Implementations of this aspect of the disclosure may include
one or more of the following features. The method further including
receiving sensor data from an external sensor. The method further
including receiving self-reported data. The method where the sensor
data includes data indicative of the posture of the patient, motion
data of the patient, electroencephalogram (EEG) data,
electrocardiogram (ECG) data, apnea hypopnea index (AHI) data or
blood-oxygen saturation data. The method where the sensor data
includes data from one or more three-axis accelerometers. The
method where the sensor data includes respiration rate data, heart
rate data, total sleep time data, sleep efficiency data, sleep
stage data, arousals data, or awakenings data. The method where the
implanted device selected from the group including of a pacemaker,
an implantable cardiac defibrillators (ICD), a cardiac
resynchronization therapy (CRT) device, and an implantable
neurostimulator (INS). The method further including a neural
network performing the analysis of the received data. The system
further including one or more external sensors configured to
transmit sensor data to the server or the external programmer. The
system further including a user-interface presented on the external
programmer and configured to receive self-reported data. The system
where the sensor outputs data indicative of the posture of the
patient, motion of the patient, an electroencephalogram (EEG), an
electrocardiogram (ECG), an apnea hypopnea index (AHI) or
blood-oxygen saturation. The system where the sensor is included of
one or more three-axis accelerometers. The system where the sensor
outputs data indicative of respiration rate, heart rate, total
sleep time, sleep efficiency, sleep stage, arousals, or awakenings.
The system where the implanted device selected from the group
including of a pacemaker, an implantable cardiac defibrillators
(ICD), a cardiac resynchronization therapy (CRT) device, and an
implantable neurostimulator (INS). The system further including a
neural network performing the analysis of the received data at the
server,
[0006] A further aspect of the disclosure is directed to a system
including: an implantable device including a sensor, a telemetry
circuit and a memory; an external programmer in communication with
the telemetry circuit and configured to receive data collected by
the sensor and stored in the memory; a server, including a
processor, in communication with the external programmer and
storing thereon an application including Instructions that when
executed by the processor executes steps of. The system also
includes receiving the data collected by the sensor from the
external programmer. The system also includes analyzing the
received data collected by the sensor. The system also includes
transmitting to a remote computer an assessment of the received
sensor data, where the assessment includes an evaluation of sleep
apnea for patient in which the implantable device has been
implanted. Other embodiments of this aspect include corresponding
computer systems, apparatus, and computer programs recorded on one
or more computer storage devices, each configured to perform the
actions of the methods and systems described herein.
[0007] Yet a further aspect of the disclosure is directed to a
computer readable recording medium storing thereon instructions
that when executed by a processor and cause the processor to
execute the steps of: receiving sensor data from an external
processor, the sensor data having been collected by an implanted
device configured for treatment of a heart related disease;
analyzing the received sensor data; and transmitting to a remote
computer an assessment of the received sensor data, where the
assessment includes an evaluation of sleep apnea for a patient in
which the implantable device has been implanted. Other embodiments
of this aspect include corresponding computer systems, apparatus,
and computer programs recorded on one or more computer storage
devices, each configured to perform the actions of the methods and
systems described herein.
[0008] Implementations of this aspect of the disclosure may include
one or more of the following features. The computer readable
recording medium where the sensor data includes data indicative of
the posture of the patient, motion data of the patient,
electroencephalogram (EEG) data, electrocardiogram (ECG) data,
apnea hypopnea index (AHI) data or blood-oxygen saturation data.
The computer readable recording medium where the sensor data
includes data from one or more three-axis accelerometers. The
computer readable recording medium where the sensor data includes
respiration rate data, heart rate data, total sleep time data,
sleep efficiency data, sleep stage data, arousals data, or
awakenings data. Implementations of the described techniques may
include hardware, a method or process, or computer software on a
computer-accessible medium, including software, firmware, hardware,
or a combination of them installed on the system that in operation
causes or cause the system to perform the actions. One or more
computer programs can be configured to perform particular
operations or actions by virtue of including instructions that,
when executed by data processing apparatus, cause the apparatus to
perform the actions.
BRIEF DESCRIPTION OF THE DRAWINGS
[0009] FIG. 1 is a conceptual diagram of an implantable device in
accordance with one aspect of the disclosure;
[0010] FIG. 2 is a conceptual diagram of a system in accordance
with the present disclosure; and
[0011] FIG. 3 depicts a flow chart for collecting, transmitting,
and analyzing data derived from the implantable device of FIG.
1.
DETAILED DESCRIPTION
[0012] This disclosure is directed to systems and methods of
improved sleep apnea diagnosis and monitoring using data collected
from implanted devices.
[0013] As noted above, many forms of heart disease are co-morbid
with sleep apnea. Typically sleep apnea is diagnosed using a sleep
study or polysomnography (PSG). A typical PSG requires at least six
hours of data collection and is usually undertaken in a clinical
environment. As part of a PSG a variety of data is collected
including an electroencephalogram (EEG) data (brain wave activity),
an electroculogram (EOG) data (measuring eye and chin movements),
electrocardiogram (ECG) data (heart rate and rhythm), respiration
rate data, and blood oxygen saturation level data, airflow from the
nose and mouth, and leg movement data, and snoring data. From these
data further observations and determinations can be made including
total sleep time (TST), sleep efficiency and latency (total sleep
time compared to total recording time), sleep states, number of
arousals (wakefulness less than 15 seconds), awakenings
(wakefulness greater than 15 seconds), an Apnea Hypopnea Index
(AHI) value.
[0014] The AHI is the number of apneas or hypopneas recorded during
the study per hour of sleep. It is generally expressed as the
number of events per hour. Based on the AHI, the severity of OSA is
classified as follows in Table 1:
TABLE-US-00001 TABLE 1 Severity Events None/Minimal: <5 per hour
Mild: >5, but <15 per hour Moderate: .gtoreq.15, but <30
per hour Severe: .gtoreq.30 per hour
[0015] While such PSG testing is the gold standard for determining
whether a patient suffers from sleep apnea, this testing has a
number of disadvantages. First, the patient themselves may not have
a clear understanding that that they suffer from sleep apnea and
may not seek out testing. Indeed, one of the oft reported reasons
that a patient seeks testing is due to pressure from a spouse or
partner who themselves may be suffering from the patient's snoring
and other sleep apnea activities. Second, while the testing is
being constantly monitored and the sleep conditions are being
monitored, the recording must necessarily be done in an environment
that is unfamiliar to the patient (resulting is potentially biased
results). Third, due to all of the equipment being employed, the
variety of wires, electrodes, and sensors can be uncomfortable and
result in poor sleep. Finally, this type of testing with all of the
equipment involved, the need for constant monitoring, and the time
and expertise necessary to analyze the data can be quite
expensive.
[0016] A wide variety of implantable devices are employed in
assessing and applying therapy to patients suffering from various
conditions. Common implantable devices include pacemakers, an
implantable cardiac defibrillators (ICD), and cardiac
resynchronization therapy (CRT) devices. In the case of pacemakers
and ICDs these may be either single or dual chamber devices. In
addition, more recently there have been developed implantable
neurostimulators such as those used for the treatment of OSA by
delivering therapy directly to the lingual muscles of a patient's
tongue. All these implantable devices include a variety of sensors
to collect various physiological data from the patient. Utilization
of the data generated by these implantable devices provides an
improved and largely automated system and method of assessing sleep
apnea in patients having these implantable devices and is described
in greater detail below.
[0017] FIG. 1 is a schematic diagram of an implantable device 10 in
accordance with the disclosure. Implantable device 10 includes a
control circuit 20, memory 30, therapy delivery circuit 40, a
sensor 50, telemetry circuit 60 and power source 70. Power source
70 may include one or more rechargeable or non-rechargeable
batteries for supplying electrical current to each of the control
circuit 20, memory 30, therapy delivery circuit 40, sensor 50 and
telemetry circuit 60. While power source 70 is shown in
communication only with control circuit 20 for the sake of clarity,
it is to be understood that power source 70 provides power as
needed to each of the circuits and components of implantable device
10 as needed. For example, power source 70 provides power to
therapy delivery circuit 40 for generating electrical stimulation
pulses.
[0018] Sensor 50 may include one or more separate sensors for
monitoring a patient condition. These sensors may include one or
accelerometers, inertial measurement units (IMU), fiber-Bragg
gratings (e.g., shape sensors), optical sensors, acoustic sensors,
pulse oximeters, and others without departing from the scope of the
disclosure and as will be described in greater detail below.
[0019] The functional blocks shown in FIG. 1 represent
functionality included in an implantable device 10 such as those
described above. The implantable device 10 may include any discrete
and/or integrated electronic circuit components that implement
analog and/or digital circuits capable of producing the functions
attributed to a pulse generator herein. The various components may
include an application specific integrated circuit (ASIC), an
electronic circuit, a processor (shared, dedicated, or group) and
memory that execute one or more software or firmware programs, a
combinational logic circuit, state machine, or other suitable
components or combinations of components that provide the described
functionality. Providing software, hardware, and/or firmware to
accomplish the described functionality in the context of any modern
medical device system, given the disclosure herein, is within the
abilities of one of skill in the art.
[0020] Control circuit 20 communicates, e.g., via a data bus, with
memory 30, therapy delivery circuit 40, telemetry circuit 60 and
sensor 50 to control the delivery of therapy other functions. As
disclosed herein, control circuit 20 may pass control signals to
therapy delivery circuit 40 to cause therapy delivery circuit 40 to
deliver electrical stimulation pulses via electrodes 80a-80d
according to a therapy protocol. Control circuit 20 may further be
configured to pass therapy control signals to therapy delivery
circuit 40 including stimulation pulse amplitude, stimulation pulse
width, stimulation pulse number and frequency of a stimulation
pulse train.
[0021] Memory 30 may store instructions for execution by a
processor included in control circuit 20, stimulation control
parameters, and other device-related or patient-related data.
Control circuit 20 may retrieve therapy delivery control parameters
and a therapy delivery protocol from memory 30 to enable control
circuit 20 to pass control signals to therapy delivery circuit 40
for controlling therapy. Memory 30 may store historical data
relating to therapy delivery for retrieval by a user via telemetry
circuit 60. Therapy delivery data or information stored in memory
30 may include therapy control parameters used to deliver
stimulation pulses as well as delivered therapy protocol(s), hours
of therapy delivery or the like. Patient related data, such as that
received from the sensor 50 signal may be stored in memory 30 for
retrieval by a user or other system components as described in
greater detail below.
[0022] Therapy delivery circuit 40 may include a charging circuit
42, an output circuit 44, and a switching circuit 46. Charging
circuit 42 may include one or more holding capacitors that are
charged using a multiple of the battery voltage of power source 70,
for example. The holding capacitors are switchably connected to
output circuit 44, which may include one or more output capacitors
that are coupled to a selected bipolar electrode pair via switching
circuit 46. The holding capacitor(s) are charged to a programmed
pacing pulse voltage amplitude by charging circuit 42 and
discharged across the output capacitor for a programmed pulse
width. Charging circuit 42 may include capacitor charge pumps or an
amplifier for the charge source to enable rapid recharging of
holding capacitors included in charging circuit 42. Therapy
delivery circuit 40 responds to control signals from control
circuit 20 for generating and delivering trains of pulses as
therapeutic pulses to the electrodes 80a-80d.
[0023] Output circuit 44 may be selectively coupled to bipolar
pairs of electrodes 80a-80d via switching circuit 46. Switching
circuit 46 may include one or more switches activated by timing
signals received from control circuit 20. Electrodes 80a-80d may be
selectively coupled to output circuit 44 in a time-varying manner
to deliver stimulation to different portions of the protrusor
muscles at different time to avoid fatigue, without requiring
stimulation to be withheld completely. Switching circuit 46 may
include a switch array, switch matrix, multiplexer, or any other
type of switching device(s) suitable to selectively couple therapy
delivery circuit 40 to electrodes 80a-80d.
[0024] Telemetry circuit 60 may be included to enable bidirectional
communication with an external programmer 90. A user, such as the
patient, may manually adjust therapy control parameter settings,
e.g., as described in Medtronic's Patient Programmer Model 37642,
incorporated by reference in its entirety. The patient may make
limited programming changes such as small changes in pulse
amplitude and pulse width. The patient may turn the therapy on and
off or to set timers to turn the therapy on or off using external
programmer 90 in wireless telemetric communication with telemetry
circuit 60.
[0025] In other examples, a user, such as a clinician, may
interacts with a user interface of an external programmer 90 to
program implantable device 10 according to a desired therapy
protocol. For example, a Physician Programmer Model 8840 available
from Medtronic, Inc., Minneapolis, Minn., may be used by the
physician to program the implantable device 10.
[0026] Programming of implantable device 10 may refer generally to
the generation and transfer of commands, programs, or other
information to control the operation of the implantable device 10.
For example, external programmer 90 may transmit programs,
parameter adjustments, program selections, group selections, or
other information to control the operation of implantable device
10, e.g., by wireless telemetry. As one example, external
programmer 90 may transmit parameter adjustments to support therapy
changes. As another example, a user may select programs or program
groups. A program may be characterized by an electrode combination,
electrode polarities, voltage or current amplitude, pulse width,
pulse rate, therapy duration, and/or pattern of electrode selection
for delivering patterns of alternating portions of the protrusor
muscles that are being stimulated. A group may be characterized by
multiple programs that are delivered simultaneously or on an
interleaved or rotating basis. These programs may adjust output
parameters or turn the therapy on or off at different time
intervals.
[0027] In some cases, external programmer 90 may be characterized
as a physician or clinician programmer if it is primarily intended
for use by a physician or clinician. In other cases, external
programmer 90 may be characterized as a patient programmer if it is
primarily intended for use by a patient. A patient programmer 90 is
generally accessible to patient and, in many cases, may be a
portable device that may accompany the patient throughout the
patient's daily routine. In general, a physician or clinician
programmer may support selection and generation of programs by a
clinician for use by implantable device 10, whereas a patient
programmer may support adjustment and selection of such programs by
a patient during ordinary use.
[0028] External programmer 90 may present patient related and/or
device related data retrieved from memory 30 via telemetry circuit
60. For example, the patient related data may be a variety of
sensor data received from sensor 50 and stored in memory 40. These
data may be presented on one or more user interfaces via a display
found on the external programmer 90 or in communication with the
external programmer.
[0029] As will be apparent to those of skill in the art, the sensor
50, which may of course be any number of separate sensors, is a
significant aspect of the disclosure. For example, the sensor 50
may be a blood-oxygen saturation sensor. This may be an optical
sensor and configured as either a reflectance blood-oxygen
saturation sensor or a transmissive blood-oxygen saturation sensor.
In the case of the transmissive blood-oxygen sensor a light source
may be formed as part of a cuff designed to surround a blood
vessel. A photodetector may be configured on an opposite side of
the cuff from the light source. Other configurations of the
blood-oxygen saturation sensor either within a body of the
implantable device 10 or operably connected there are also
considered within the scope of the disclosure. Indeed, in
accordance with the disclosure, the blood-oxygen saturation sensor
may be entirely separate from the implantable device 10 and simply
an external sensor applied to the finger of the patient, but in
communication with the external programmer 90.
[0030] A further sensor 50 may be a motion detector. The motion
detector may be an accelerometer, for example a three-axis
accelerometer. This motion detector may be tuned to detect motion
caused by movement of the patient, motion caused by the beating of
the heart (e.g., measuring the patient's pulse), or motion caused
by respiration (operation of the lungs) and others. For example,
the sensor 50 may be tuned to detect movement of the patient's
legs. In accordance with one aspect of the disclosure this might be
detected motion that which is inconsistent with heart rate movement
or respiration movement and does not result in a change in posture
of the patient. Still further, the three-axis accelerometer may be
tuned to detect snoring. Again, band pass filtering can be employed
to remove all but the high frequency input that is associated with
snoring.
[0031] The sensor 50 may be a posture detector. As a posture
detector, a three-axis accelerometer can be employed to detect when
the patient is in a reclined or sleeping position and even whether
the patient is laying prone or supine or laying on their right or
left sides. The effect of 1G of gravitational acceleration applied
directly along an axis of a stationary accelerometer provides a
characteristic output voltage signal having an amplitude that can
be referenced or scaled as +1 for angular computation purposes. The
effect of 1 G of gravitational acceleration applied in precisely
the opposite or negative direction to the sensitive axis provides a
characteristic output voltage signal amplitude that is referenced
or scaled as -1. If the axis is oriented transverse to the
direction of the gravitational force, a bias voltage level output
signal should be present, and that voltage signal level is
referenced or scaled as 0. The degree to which the axis is oriented
away or tilted from the direction of the gravitational force can
also be detected by the magnitude and polarity of the output
voltage signal level deviating from the bias level scaled to 0 and
below the output signal level values scaled to +1 and -1. Other
scales may be employed, depending on the signal polarities and
ranges employed. The sensor 50 may include its own microprocessor
with autocalibration of offset error and drift (possibly caused by
temperature variation or other things).
TABLE-US-00002 TABLE 2 Posture a.sub.x a.sub.y a.sub.z UP 0 +1 0
SUPINE 0 0 +1 PRONE 0 0 -1 RIGHT -1 0 0 LEFT +1 0 0
[0032] Table 2 sets forth the ideal, scaled amplitudes of the
output signals, ax, ay, and az, respectively, of a three-axis
accelerometer employed in sensor 50 and incorporating into
implantable device 10. (The units in the ideal example would be in
gravity or "g"). One axis of the accelerometer (a.sub.y) is aligned
to earth's gravitational field when the implantable device 10 is
implanted. Thus, when standing upright and remaining still, the
amplitude or level of the output signal a.sub.y of three-axis
accelerometer should be at +1. In this orientation, the scaled
amplitudes of the output signals az and ax of the three-axis
accelerometer, respectively, should approach 0.
[0033] The scaled amplitude of the output signal az of the
three-axis accelerometer should approach +1 or -1, respectively,
when the patient lies still and is either supine or prone on their
back or stomach and if the INS 10 is implanted with the z-axis of
the three axis accelerometer aligned in a posterior-anterior
position. In these positions, the amplitudes of the output signals
a.sub.y and ax of the three-axis accelerometer, respectively,
should approach 0. In the same fashion, the patient lying on the
right and left sides will orient the sensitive axis of the
three-axis accelerometer with earth's gravitational field to
develop the scaled amplitude of either -1 or +1 of the output
signal a.sub.x. The amplitudes of the output signals a.sub.y and
a.sub.z of the three-axis accelerometer should approach 0. In these
ideal orientations of Table 2, there is no rotation of the axes of
the INS 10 with respect to earth's gravitational field.
[0034] As will be appreciated, the determination described above
identifies the pose of the implantable device 10 and not
necessarily the patient in which it is implanted. In practice the
implantable device 10 will rarely if ever be implanted in the
patient such that the three axes of the three-axis accelerometer
precisely align the idea orientations of Table 1. Accordingly,
following implantation of the implantable device 10, a series of
calibration tests can be undertaken during which the patient is
alternated from standing to lying, from prone to supine, and from
right to left sides. By acquiring a series of such values, the
sensor 50 can be calibrated for the implantation, to determine the
voltage output values of each of the three axes of the
accelerometer in each of the positions. Further, though not
described in detail herein, similar analyses may be undertaken to
determine when a person is in a slightly reclined position such as
when sitting in an airplane seat or other position.
[0035] In another sensor 50, a three-axis accelerometer acts, as
noted above, as a motion detector. This motion detector is tuned
(e.g., using one or more band pass filters) to detect lung
vibrations in the patient caused by respiration.
[0036] The sensor 50 may be an ECG sensor. ECG is a recording of
the electrical activity of the heart over a period of time. While
an ECG typically employs sensors placed on the skin, an effective
ECG can be employed in an implantable device wherein at least two
electrodes separated by a distance (e.g., at least about 35 mm) are
employed to detect electrical changes caused by the cardiac
depolarization and repolarization during each cardiac cycle.
[0037] Yet a further sensor 50 that may be employed is an EEG
system from which the sleep stages of the patient may be
determined. The EEG may include sensors implanted in the patient
and operably connected to the implantable device 10. Alternatively,
the sensors may be implanted in the patient and operably connected
to a remove or satellite implanted device located above the
shoulders of the patient and in communication with the implantable
device 10. Still further the sensors may be a wearable set of
sensors that are in communication with the implantable device.
[0038] In view of inclusion of one or more of these sensors 50, a
corollary set of data can be constructed to that from a sleep
study. For example, the total sleep time (TST) can be derived by
comparing the time period that the patient (an implantable device
10) is in a lying down position, either prone or supine, and the
time where the motion sensor detects motion consistent with a
sleeping heart rate, or with motion consistent with sleeping. Once
a TST is determined, a sleep efficiency can also be derived by
comparing the TST to the total recording time (TRT) which may be
the entirety of the period that the patient is in the lying down
position.
[0039] Sleep stages, as in the case of a formal sleep study might
require the use of EEG data from the EEG sensors, however, arousals
or awakenings can be derived from the posture sensor. These would
be instances where the patient transitioned from one to another
posture and depending on the period of time between the beginning
of the transition the transition can be characterized as an arousal
or awakening. Gross motion data from a motion sensor, consistent
with for example walking to the bathroom, or other data can also be
overlaid on the data from the posture detector to further assist in
classifying the detected movements or change in posture as an
awakening or an arousal.
[0040] Respiration rate may be derived by a number of methods. As
noted above, a three-axis accelerometer may be tuned to the
vibrations of the lungs. By such tuning the change in position of
the sensor 50 can be plotted and normalized to provide a
respiration rate for the patient. Further ECG data, as might be
acquired from ECG sensors is known to be proportional to
respiration rate. In this way as the ECG baseline shifts, as a
result of increased heart rate, a proportion change in respiration
rate can be determined. Similarly, an optical sensor, such as the
reflectance blood-oxygen saturation sensor described above to
measure blood-oxygen saturation levels may also be employed to
determine a pulse transit time. A shift in this transit time is
also known to be proportional with a chance in respiration rate.
For both the ECG baseline and optical sensor baseline shifts, a
normal range of both of these values for the patient while sleeping
may be required to determine these changes in respiration rate.
[0041] With respect to the respiration rate, any or all of these
respiration rates may be employed to develop an AHI value. By
comparing changes in the lung vibration, and changes in the
baseline of the ECG and pulse transit times, an initial
approximation of instances of an apnea can be identified. When any
of these occur, the blood-oxygen saturation level sensor can be
triggered to record the blood-oxygen saturation level for a given
period of time following the event (assuming it is not being
constantly monitored). Where a change in respiration rate is
observed, if it is followed by a drop in blood-oxygen saturation
level, it can reasonably be identified as an apnea, as described
above with respect to Table 1. As those are measured on any given
night's sleep and over the course of days, weeks, and years the
development of and the incidence of sleep apnea can be assessed and
actively monitored by health care providers in coordination with
the treatment of the co-morbid heart conditions.
[0042] Though described herein largely in the context of sensors 50
that form part of the implantable device 10, this instant
disclosure is not so limited. As noted elsewhere one or more of the
sensors including the EEG sensors, the leg movement sensors, the
ECG sensor, the blood-oxygen saturation level sensor, and others
may be external sensors 100 (FIG. 2) formed external to the patient
and the implantable device without departing from the scope of the
disclosure. These external sensors 100 may be in communication the
external programmer 90 or directly with a remote server (e.g., a
cloud-based data system).
[0043] A further aspect of the disclosure is described in
connection with FIGS. 2 and 3 in which a simplified diagram of a
system 200 is depicted, and a method of the systems operation are
described. The system 200 includes an implantable device 10, an
external programmer 90, one or more external sensors 100, a remote
server 202 in communication with the external programmer 90,
external sensors 100, and a remote computer 204. Those of ordinary
skill in the art will appreciate that the remote computer 204 may
be an external programmer 90, particularly one configured for use
by a health care provider.
[0044] Following implantation of the implantable device 10, (step
700) the data collected from sensor 50 is downloaded to the
external programmer 90 (step 710). This data from the sensor 50 may
be combined with various self-reported data that a user may input
via a user interface on the external programmer 90 (step 720). In
one embodiment of the disclosure the external programmer 90, or
another device (not shown) in communication with the server 202,
presents the patient with a user interface. The user interface may
be presented to the user on a periodic basis including daily,
weekly, bi-weekly, or monthly. In accordance, with the daily
embodiment, the user interface may request that the patient input
various self-reporting data. Data from external sensors 100 or
other appliances may also be reported either to the external
programmer 90 or directly to the remote server 202.
[0045] As noted above, the sensor 50 can provide a variety of data
dependent upon how it is configured. The sensor 50 can be a motion
sensor, heart rate detector, ECG sensor, EEG sensor, posture
detector, blood-oxygen saturation detector, respiration rate
detector, leg movement sensor, and others. These sensors may be
formed of various sub-components including, but not limited to
accelerometers tuned to detect specific types movement and
vibrations as disclosed elsewhere herein.
[0046] As one example using the posture detection data, either
alone or in combination with heart rate or respiration rate, a
sleep start and end time may be determined. Using one or more
accelerometers and a variety of bandpass filtering position,
activity (arousals vs awakenings), sleep stages, respiration rate,
and heart rate can be collected. This data can be reported to the
control circuit 20 and stored in memory 30 at least temporarily.
The external programmer 90 can be set to automatically interface
with the implantable 10 every day, every hour, or at another
periodic or scheduled interval. The external programmer 90
downloads the sensor data via the telemetry circuit 60 (step 710)
and receives the external sensor data and self-reported data at
step 720. The external programmer may optionally communicate the
sensor data from the implantable device and any and self-reported
data entered via the user-interface to the server 202 (step
725).
[0047] Either the server 202 or the external programmer 90 may
include thereon one or more software applications. One of these
applications may review the data received from the external
programmer 90 and assess whether the patient having the implantable
device 10 shows indications of suffering from sleep apnea. For
example, a patient who registers a low sleep efficiency (TST/TRT)
value, a relatively high number of arousals or awakenings, an AHI
value of greater than 15, and drops in blood-oxygen saturation
levels following each occurrence of an apnea would provide strong
indication that the patient suffers from at least moderate sleep
apnea. The application running on the external programmer 90 or
server 202 may analyze these and other data at step 730 and report
an assessment to a health care provider via remote computer 204 at
step 740 or directly to the patient via the user interface on the
external programmer 90 at steps 750. This collection of data and
determining of a sleep score (steps 710-730) may be iterative
repeated prior to advancing to the next step.
[0048] Either the healthcare provider, accessing the remote
computer 204, can receive the assessment from the server 202 via
the remote computer. This may be as part of assessing other data
related to the patient. For example, where the implantable device
10 is pacemaker, the health care provider may periodically analyze
the heart rhythms and interventional actions of the pacemaker. On a
user interface presented to the health care provider via the remote
computer 204, in addition to the standard heart related data
related directly to the implantable device 10, an alert or other
indication may be presented to the health care provider indicating
that the application has determined that the patient may suffer
from to common comorbidity of sleep apnea.
[0049] The remote computer 204 also provides access to the raw data
and computed data derived from the data collected by the sensor 50
and from external sensors 100 (described above). Thus, the health
care provider can analyze the collected and computed data in much
the same manner as a health care provider might analyze the data
collected during a traditional sleep study, as described above.
[0050] Whether relying on the indication provide by the application
running on the server 202 or based on the health care provider's
own assessment of the data the health care provider can initiate
communications with the patient. As will be appreciated the
communication can range from relying solely on the data collected
via the sensor 50 of the implantable device 10 and external sensors
100 to start a treatment regimen for sleep apnea to scheduling a
formal sleep study.
[0051] Similarly, the application running on the external
programmer 90 can present one or more user interfaces to the
patient where an initial assessment of the patient's likelihood of
suffering from sleep apnea can be indicated. This may include an
indication of the sleep score the patient received for the prior
night's sleep, historical comparison of their sleep score and even
access to some or all of the raw data from which the sleep score is
derived. Further, the user interface may present a suggestion to
contact their health care provider, an opportunity to make an
appointment with their health care provider, or even access to
emergency services if warranted. In addition, even in instances
where the sleep score and other determinations are made on the
external programmer 90, the external programmer may nonetheless be
in communication with the server 202 to enable further processing
and storage of the data the external programmer 90 has
analyzed.
[0052] In a further aspect of the disclosure, the server 202 may
collect or be in communication one or more further servers
receiving similar data from other patients. The entirety of the
collected data may then be analyzed by one or more neural networks
to assess the combined data and to identify patterns within the
data to provide indications to health care providers related to
both an individual patient that may require treatment and therapy,
and to provide a global assessment of a larger population of
patients. Some of these patients will have similar comorbidities,
and others will not. By further assessment of the data the neural
network can seek out similar groups of patients and provide
information to health care providers regarding the likelihood of
sleep apnea even before implantation of the implantable device
based on these similarities (e.g., age, demographics, weight, heart
disease, blood pressure, etc.). Further, the data from the
implantable devices can be constantly assessed by the neural
networks to assess the population of patients having implantable
devices to diagnose sleep apnea co-morbidities. Additionally or
alternatively, the server 202 may include one or more applications
employing fuzzy logic to analyze the data from both an individual
and from the broader community of patients (step 730).
[0053] As a further aspect of the present disclosure, prior to
implantation of an implantable device 10, the patient may have
already undergone a patient assessment of sleep apnea with their
health care provider. During this assessment a variety of
self-reported issues may be identified including daytime
sleepiness, interrupted snoring, gasping, co-morbidities, etc. The
data related to these issues may be stored on the server 202 as
part of the patient electronic medical records (EMR), these data
may also be analyzed as part of the application's assessment of the
data received from sensor 90. Further, the EMR may include the
results of a prior sleep study undertaken by the patient. These
data may be recorded by a remote computer 204, either directly or
via additional hardware, and saved to the remote server 202.
[0054] As will be appreciated, sleep apnea is a degenerative
disease in that it manifests itself and worsens over time. Thus,
even if an in initial sleep study is inconclusive, or does not
result in treatment for sleep apnea, over time the patient's
condition may worsen and require treatment as a result of or in
conjunction with the worsening of their co-morbid conditions.
[0055] Though generally having been described herein as having been
undertaken at the server 202, any of the calculations and analyses
of the sensor data from sensor 50 and described herein can be
undertaken by the control circuit 20 or by an application running
on the external programmer 90. In this manner the results of these
calculations, along with any of the direct sensor data may be
displayed to a patient or a health care provider on the external
programmer 90 as part of a user interface displayable therein. This
may include an indication to the patient that they display symptoms
of suffering from sleep apnea and should seek attention from their
health care provider. Similarly, even if the calculations and
analyses are performed by one or more applications running on the
server 202, because the server 202 is in communication with
external programmer 90 the results of those calculations and
analyses may be transmitted back to the external programmer 90 and
presented to the patient on a user interface displayable thereon.
Again, this may include an indication to the patient that they
appear to display symptoms of sleep apnea and should seek attention
from their health care provider.
[0056] It should be understood that, depending on the example,
certain acts or events of any of the methods described herein can
be performed in a different sequence, may be added, merged, or left
out altogether (e.g., not all described acts or events are
necessary for the practice of the method). Moreover, in certain
examples, acts or events may be performed concurrently, e.g.,
through multi-threaded processing, interrupt processing, or
multiple processors, rather than sequentially. In addition, while
certain aspects of this disclosure are described as being performed
by a single module or unit for purposes of clarity, it should be
understood that the techniques of this disclosure may be performed
by a combination of units or modules associated with, for example,
a medical device.
[0057] In one or more examples, the functions described may be
implemented in hardware, software, firmware, or any combination
thereof. If implemented in software, the functions may be stored as
one or more instructions or code on a computer-readable medium and
executed by a hardware-based processing unit. Computer-readable
media may include computer-readable storage media, which
corresponds to a tangible medium such as data storage media (e.g.,
RAM, ROM, EEPROM, flash memory, or any other medium that can be
used to store desired program code in the form of instructions or
data structures and that can be accessed by a computer).
[0058] Instructions may be executed by one or more processors, such
as one or more digital signal processors (DSPs), general purpose
microprocessors, application specific integrated circuits (ASICs),
field programmable logic arrays (FPGAs), or other equivalent
integrated or discrete logic circuitry. Accordingly, the term
"processor," as used herein may refer to any of the foregoing
structure or any other structure suitable for implementation of the
techniques described herein. Also, the techniques could be fully
implemented in one or more circuits or logic elements.
[0059] Thus, an implantable medical device system has been
presented in the foregoing description with reference to specific
examples. It is to be understood that various aspects disclosed
herein may be combined in different combinations than the specific
combinations presented in the accompanying drawings. It is
appreciated that various modifications to the referenced examples
may be made without departing from the scope of the disclosure and
the following claims.
* * * * *