U.S. patent application number 15/174476 was filed with the patent office on 2016-09-29 for system and method for guidance of anesthesia, analgesia and amnesia.
The applicant listed for this patent is New York University. Invention is credited to Erwin R. JOHN, Leslie S. PRICHEP.
Application Number | 20160278697 15/174476 |
Document ID | / |
Family ID | 32106639 |
Filed Date | 2016-09-29 |
United States Patent
Application |
20160278697 |
Kind Code |
A1 |
JOHN; Erwin R. ; et
al. |
September 29, 2016 |
System and Method for Guidance of Anesthesia, Analgesia and
Amnesia
Abstract
A method for monitoring anesthetization of a patient, includes
the steps of removably connecting a plurality of electrodes to the
scalp of the patient and administering sufficient anesthesia to the
patient so that the patient attains a plane of anesthesia selected
by an operator. The brain waves of the patient are then amplified
and digitized after the patient has been anesthetized, before
beginning the medical procedure, to obtain a first set of digital
data. The brain waves of the patient are then amplified and
digitized during the medical procedure to provide a second set of
digital data and the first and second sets of digital data are
analyzed in at least one of a time domain and a frequency domain.
Separate trajectories are then computed from the data analysis
trajectories for at least two different indices of an anesthetic
state of the patient during the medical procedure, the indices
being selected from a group including a Depth Index (DI), a Memory
Index (MI) and a Pain Index (PI). A system for providing anesthesia
to a patient, includes a plurality of electrodes, a first
arrangement allowing an operator to administer anesthesia to the
patient until the patient has attained a selected plane of
anesthesia and a second arrangement coupled to the electrodes for
amplifying and digitizing brain waves of the patient after the
patient has been anesthetized, before the medical procedure has
been begun to obtain a first set of digital data, the second
arrangement amplifying and digitizing ongoing brain waves of the
patient during the medical procedure to provide a second set of
digital data in combination with a third arrangement analyzing the
first and second sets of digital data in at least one of a time
domain and a frequency domain, a fourth arrangement computing from
the data analysis separate trajectories for at least two different
indices of a state of the patient during the medical procedure, the
indices being selected from a group including a Depth Index (DI), a
Memory Index (MI) and a Pain Index (PI), a fifth arrangement
providing control signals when any of the trajectories indicates
that the patient is deviating from the selected plane of anesthesia
and a sixth arrangement automatically adjusting two different
anesthetic agents administered to the patient based on the control
signal to restore the patient to the selected plane of
anesthesia.
Inventors: |
JOHN; Erwin R.; (Mamaroneck,
NY) ; PRICHEP; Leslie S.; (Mamaroneck, NY) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
New York University |
New York |
NY |
US |
|
|
Family ID: |
32106639 |
Appl. No.: |
15/174476 |
Filed: |
June 6, 2016 |
Related U.S. Patent Documents
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Application
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Filing Date |
Patent Number |
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13735628 |
Jan 7, 2013 |
9357965 |
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15174476 |
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13036730 |
Feb 28, 2011 |
8352023 |
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13735628 |
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12772659 |
May 3, 2010 |
7899525 |
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13036730 |
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11471122 |
Jun 20, 2006 |
7711417 |
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12772659 |
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10279131 |
Oct 23, 2002 |
7089927 |
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11471122 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61B 5/048 20130101;
A61B 5/746 20130101; A61M 5/142 20130101; A61M 5/1723 20130101;
A61B 5/021 20130101; A61B 5/4839 20130101; A61B 5/7275 20130101;
A61B 5/7405 20130101; A61M 16/12 20130101; A61M 16/01 20130101;
A61M 2202/048 20130101; A61B 5/7257 20130101; A61B 5/04845
20130101; A61M 16/06 20130101; A61B 5/01 20130101; A61M 2230/10
20130101; A61M 5/00 20130101; A61M 16/0683 20130101; A61M 2210/0618
20130101; A61M 16/18 20130101; A61B 5/7455 20130101; A61M 16/201
20140204; A61B 5/742 20130101; A61B 5/7225 20130101; A61B 5/02028
20130101; A61M 5/1407 20130101; A61B 5/04012 20130101; A61M
2016/0661 20130101; A61B 5/08 20130101; A61B 5/4821 20130101; A61B
5/024 20130101 |
International
Class: |
A61B 5/00 20060101
A61B005/00; A61B 5/024 20060101 A61B005/024; A61B 5/02 20060101
A61B005/02; A61B 5/021 20060101 A61B005/021; A61M 16/20 20060101
A61M016/20; A61B 5/01 20060101 A61B005/01; A61M 5/142 20060101
A61M005/142; A61M 5/14 20060101 A61M005/14; A61M 5/172 20060101
A61M005/172; A61M 16/01 20060101 A61M016/01; A61B 5/0484 20060101
A61B005/0484; A61B 5/08 20060101 A61B005/08 |
Claims
1.-30. (canceled)
31. A method, comprising: administering to a patient a first
interventional agent until the patient attains a first desired
level of sensitivity to pain; amplifying and digitizing brain waves
of the patient before and at a first time after the administering
step to generate a first set of digital data; amplifying and
digitizing brain waves of the patient at a second time subsequent
to the first time to generate a second set of digital data;
computing a first trajectory for a first pain index as a function
of a comparison of the first and second sets of digital data, using
a processor; determining, using the processor, a recommended rate
of delivery of the first interventional agent to the patient as a
function of the first trajectory, wherein the first interventional
agent is one of an anesthetic, analgesic and amnesic agent; and
outputting to a user the recommended rate of delivery of the first
interventional agent.
32. The method of claim 31, further comprising the step of
computing a second trajectory for a second pain index as a function
of a comparison of the first and second sets of digital data, using
a processor.
33. The method of claim 31, further comprising the step of
administering to a patient a second interventional agent until the
patient attains a second desired level of sensitivity to pain, the
second interventional agent being another one of an anesthetic,
analgesic and amnesic agent.
34. The method of claim 31, further comprising the step of
displaying, via a display, data corresponding to power spectra from
each of a plurality of electrodes connected to the patient.
35. The method of claim 31, further comprising the step of using
data gathered from of a plurality of electrodes connected to the
patient to define a self-norm for the patient.
36. The method of claim 35, further comprising the step of
comparing subsequent data gathered from the electrodes to the
self-norm.
37. The method according to claim 35, wherein the data corresponds
to one of absolute and relative power within each of the plurality
of electrodes continuously and within selected frequency bands.
38. A system, comprising: a storage unit having a first set of
digital data generated by amplifying and digitizing brain waves of
the patient before and at a first time after administration of a
first interventional agent to the patient in an amount that attains
a first desired level of sensitivity to pain, and a second set of
digital data generated by amplifying and digitizing brain waves of
the patient at a second time subsequent to the first time; a
processor computing a first trajectory for a first pain index as a
function of a comparison of the first and second sets of digital
data and determining a recommended rate of delivery of the first
interventional agent to the patient as a function of the first
trajectory, wherein the first interventional agent is one of an
anesthetic, analgesic and amnesic agent; and a display outputting
the recommended rate of delivery of the first interventional
agent.
39. The system of claim 38, further comprising a plurality of
electroencephalogram (EEG) electrodes coupled to a scalp of the
patient and producing electrical signals corresponding to brain
waves of the patient.
40. The system of claim 39, wherein the first and second sets of
digital data are generated by amplifiers amplifying the electrical
signals, an analog-to-digital multiplexer converting the amplified
electrical signals into digital signals and a distal signal
processor executing a signal processing algorithm on the digital
signals.
Description
FIELD OF THE INVENTION
[0001] The present invention relates to medical systems and methods
and more particularly, to an electroencephalograph ("EEG") based
system for monitoring or automatic guidance of anesthesia,
analgesia, and amnesia during surgical operations.
BACKGROUND INFORMATION
[0002] Anesthetic drugs which, when properly administered, induce
loss of awareness, are often used for painful and serious medical
procedures such as surgical operations. A general anesthetic, when
properly administered, will cause a progressive depression of the
central nervous system so that the patient loses consciousness. A
local anesthetic, however, only affects sensation at the region to
which it is applied.
[0003] Generally, the patient, prior to a surgical operation, is
anesthetized by a specialized medical practitioner
("anesthesiologist") who may be a Board Certified physician, or a
specially trained nurse anesthetist. One or more volatile
inhalational liquids or gases may be administered (e.g., nitrous
oxide, methoxy flurane, sevoflurane, isoflurane, desflurane,
ethylene, cyclopropane, ether chloroform, halothane, etc.). Certain
desirable anesthetic gases such as Ciboflorane.RTM. (Abbott Lab)
may sometimes not be used because of their cost. Alternatively,
nonvolatile drugs may be administered by injection or intravenous
infusion (e.g., flumazenil, thiopentone, Retamine, remifentanyl,
midazolam, pentothal, propofol, evipal procaine and Etomidate.RTM.
(Abbott)). The objectives of general anesthesia administered prior
to a surgical operation, may include:
a) blocking the patient's movements and relaxing the patient's
muscles to prevent involuntary reflex muscle movements which may
interfere with the operation; b) preventing the patient from being
aware (i.e., loss of consciousness, or sedation) during the
operation; c) preventing the patient feeling pain (i.e., loss of
sensation, or analgesia) during the operation; and d) preventing
the patient from remembering intra-operative events or discussions
(i.e., amnesia). Furthermore, the anesthesia should not lower blood
pressure to a dangerous extent (e.g., below 50 mm Hg for mean
arterial pressure (MAP)).
[0004] These objectives of general anesthesia may often be attained
by separate administration of hypnotic or sedative, analgesic and
amnesic agents, in accordance with the clinical judgment of the
managing anesthesiologist evaluating the apparent state of the
patient and a variety of vital signs.
[0005] In order to monitor the "anesthetic depth" or "plane of
anesthesia" of the patient, a skilled anesthesiologist looks at the
vital signals of the patient (e.g., breathing, blood pressure,
etc.) to determine if more, or less, anesthetic is required. Often
he/she looks into the patient's eyes to determine the extent of the
dilation of the pupils as an indication of the level (or depth) of
the effect of the anesthesia. Complete reliance on the
availability, skill and attention of the anesthesiologist presents
problems in some situations. In addition, respiration may be
artificially controlled (e.g., by a respirator) and/or medications
may block or alter useful autonomic signs. In the absence of graded
neurological reflexes, the depth of suppression of brain activity
related to awareness often may not be accurately gauged. The mute,
paralyzed patient cannot report the experience of pain.
Furthermore, pain cannot be reliably inferred from vital signs
since they may be blocked by the presence of medications. In some
operations (e.g., heart surgery), the head is covered so that the
patient's eyes cannot be viewed and pupillary dilation is not
apparent. No reliable estimate may then be made of the possibility
that the patient may be aware of environmental events, experience
pain and/or be able to store and retrieve memories about unpleasant
experiences. Furthermore, during prolonged operations (e.g., 10 to
15 hours or more), the attention of the anesthesia nurse or
anesthesiologist may not be constant.
[0006] Also, at times, an anesthesiologist may not be available
(e.g., in emergency or battlefield situations). Similarly, in
isolated geographic locations, it may be impractical to move a
patient requiring an operation to a hospital where an
anesthesiologist would be available. However, a physician or
surgeon may be able to perform a required operation if there were
some way to effectively and safely anesthetize the patient.
[0007] U.S. Pat. No. 2,690,178 to Bickford purports to describe an
automatic system for applying anesthetic to a patient while
monitoring the patient's brain waves to monitor the effects of the
anesthetic. Bickford used an integrated potential output of the
cortex to judge the efficacy of the anesthetic. (See also, U.S.
Pat. Nos. 4,280,494 and 4,533,346 to Cosgrove et al. entitled
"System for Automatic Feedback-Controlled Administration of
Drugs"). The EEG measure used is an "EEG power response" (i.e., a
total power output of the brain). However, the use of the single
measure of integrated cortex output as described in the Bickford
and Cosgrove patents may not provide a reliable control signal for
applying a general anesthetic. Different anesthetics have different
impacts on power output and several may actually cause an increase
in a power detected by a cortical EEG. Furthermore, in some
instances, the nature of the power detected changes depending upon
electrode position. In addition, not only do different anesthetics
have different effects upon the EEG, but those effects may vary
from patient to patient as a consequence of different pre-operative
medications and/or different biochemical sensitivities.
[0008] The following patents which describe methods and apparatus
for monitoring and/or controlling the provision of anesthetic to
patients are hereby expressly incorporated by reference: U.S. Pat.
No. 6,315,736 to Tsutsumi et al.; U.S. Pat. No. 6,317,627 to Ennen
et al; U.S. Pat. No. 6,016,444 to E. R. John; U.S. Pat. No.
5,699,808 to E. R. John; U.S. Pat. No. 5,775,330 to Kangas et al.;
U.S. Pat. No. 4,557,270 to E. R. John; U.S. Pat. No. 5,010,891 to
Chamoun; and U.S. Pat. No. 4,869,264 to Silberstein.
SUMMARY OF THE INVENTION
[0009] The present invention is directed to a method for monitoring
anesthetization of a patient undergoing a medical procedure,
comprising the steps of (a) removably connecting a set of at least
two electroencephalograph ("EEG") electrodes to the scalp of the
patient, (b) administering sufficient anesthesia to the patient so
that the patient attains a plane of anesthesia selected by an
operator and (c) amplifying and digitizing brain waves of the
patient after step (b) and before beginning the medical procedure
to obtain a first set of digital data in combination with the steps
of (d) amplifying and digitizing brain waves of the patient during
the medical procedure to provide a second set of digital data, (e)
analyzing the first and second sets of digital data in at least one
of a time domain and a frequency domain; and (f) computing from the
data analysis of step (e) separate trajectories for at least two
different indices of an anesthetic state of the patient during the
medical procedure, the indices being selected from a group
including a Depth Index (DI), a Memory Index (MI) and a Pain Index
(PI), wherein the DI corresponds to a depth of anesthesia of the
patient, PI corresponds to a sensitivity of the patient to pain and
MI corresponds to an ability of the patient to form and store
memories.
BRIEF DESCRIPTION OF DRAWINGS
[0010] FIG. 1 is a block schematic drawing of an exemplary
apparatus according to the present invention.
DETAILED DESCRIPTION
[0011] The present invention utilizes electrophysiological methods
to provide automatic quantitative evaluation separately for a level
of awareness (sedation), a sensitivity to pain and/or an ability to
comprehend auditory speech and store memories of intraoperative or
environmental events. This information may be provided as a monitor
to aid an anesthesiologist in the management of an individual
patient or may be used as an input to a servo system which
automatically delivers anesthetic, analgesic and amnesic agents to
optimize the state of a patient. In particular, before an
operation, the anesthesiologist may attach a plurality of removable
EEG electrodes to the scalp of the patient (preferably, two to
eight electrodes and more preferably, five electrodes). If five
active electrodes are used, they may, for example, be placed at F1,
F2, F7 and F8 active positions as would be understood by those
skilled in the art. Reference electrodes may then be placed, for
example, at FPZ and CZ (vertex) and the cheekbone. In addition, an
earpiece insert may be used to apply audio stimulus to the patient,
and a finger cot electrode may be used to apply slight electrical
shocks as somatosensory stimulus. The anesthesiologist may then
administer a selected anesthetic to place the patient at a desired
depth of anesthesia using his clinical judgment, based upon the
patient's vital signs and clinical experience. At that time,
measurements of the patient's EEG, AER (Auditory Evoked Response)
and/or SER (Somatosensory Evoked Response) may be automatically
made to provide an adequate self-norm (reference or base line).
Measures of vital signs such as heart rate, stroke volume, blood
pressure, respiration and temperature may also be obtained and
monitored from the anesthesiology console. In addition, oxygen
saturation may be measured, for example, using an NIR sensor such
as "INVOS" .RTM. (In Vitro Optical Spectroscopy) (Somanetics). A
QEEG system, which monitors the electrophysiology of the patient,
may then be able to detect changes in the clinical state of the
patient (e.g., changes in the depth of anesthesia, sensitivity to
pain, or probability of memory storage) before there are clinical
or qualitative signs of change (e.g., movement, tachycardia, or
increased blood pressure). During the operation, the QEEG system
automatically and continually collects on-going EEG and also
challenges the patient with regularly repeated periods of stimuli
to provide evoked potentials, such as AER and SER. These data are
subjected to automatic artifact removal and features selected from
the self-norm are continuously analyzed and displayed as three
trajectories. In one embodiment of the invention, deviations beyond
confidence limits (i.e., a reference band) for any of the
trajectories, may automatically control the application of the
different agents to achieve or maintain the desired depth of
anesthesia. Alternatively, this data may be displayed to the
anesthesiologist who may then make judgments based on his
experience, etc., as to what measures are required to optimize the
anesthesia of the patient.
[0012] In accordance with one embodiment of the present invention,
a Guidance of Anesthesia, Analgesia and Amnesia System ("GAS")
includes an EEG system and automatic quantitative analysis of the
EEG ("QEEG") and sensory evoked responses. It serves as an
intra-operative multimodal monitor to inform the anesthesiologist
of the present state of anesthesia of the patient or, if desired,
to automatically administer dosages of one or more agents during an
operation to facilitate management of the patient. If an
anesthesiologist or intensivist is not available, the system may
permit a physician or paramedical personnel to manually or
automatically maintain the desired level of anesthesia in a
patient.
[0013] In contrast to conventional systems, the GAS separately
evaluates several dimensions of the state of the patient. In
addition to serving as a monitor to aid optimal manual management
of the patient, the present method and system enables an automatic
control of multiple dimensions of anesthesia. Separate measures
quantify indices for the depth of anesthesia (DI), sensitivity to
pain (Pain Index or PI) and likelihood of storage of Memory Index
(MI).
[0014] The first dimensional measure, the Depth Index (DI), relates
to a depth of anesthesia. If the patient has attained a
satisfactory depth of anesthesia, consciousness has been lost and
the patient's muscles are sufficiently relaxed so that involuntary
muscle movements do not interfere with the operation. This is an
over-all measurement of the depth of anesthesia. An example of an
agent primarily directed to attain and maintain general anesthesia
level (DI), is propofol ("Diprivan".RTM. by Zeneca Phar). The
measurement of the patient's immediate sensitivity to pain is
called the "Pain Index" (PI) and an example of an agent primarily
directed to controlling PI is remifentanyl (selective mu-opiod with
a very short half-life). The measurement of the functional state of
the patient's memory is called the "Memory Index" (MI). An example
of an agent directed primarily to control MI is midazolam
(Versed).
[0015] General anesthetics produce a progressive depression of the
central nervous system. Generally, they produce an irregular
descending paralysis of the central nervous system and suppression
of the sensory cortex. The paralysis successively affects the basal
ganglia, the cerebellum and the spinal cord; without suppression of
the medulla (respiratory and cardiac functions). The sensory input
to the cortex is suppressed because the sensory pathway from the
brain stem reticular formation and the thalamus is inhibited. The
electrical activity of every local brain region as well as
interactions among regions is auto-regulated by a complex
neuroanatomical homeostatic system, producing an EEG power spectrum
which is generally predictable in healthy persons of any age and
independent of ethnic background, in the absence of perturbing
illnesses or chemical substances. Serial measurements are extremely
stable and reproducible within any individual. Anesthetic agents
alter the relationships within the homeostatic system, producing
certain changes in the power spectrum, which have been shown to be
invariant with loss of consciousness caused by any agent but
reversible with the return of consciousness. Anesthetics act upon
pacemaker oscillator cells which normally regulate the stable
spontaneous EEG rhythm, generating a power spectrum with a peak
that is generally in the center of the Alpha band (8-12 Hz)) via
the nucleus reticularis. This inhibits the thalamus via the
neurotransmitter gamma-amino butyric acid and, in effect, closes
the sensory gate to the cortex. The pacemaker cells are
hyperpolarized by this inhibitory influence of n. reticularis,
thereby slowing their oscillations to produce slower Alpha waves
and enhancement of Theta waves. The slower Alpha waves and Theta
waves, and other distinctive alterations of the patient's normal
regional EEG power spectra, and electrophysiological signs of
interactions between regions, may be detected by the QEEG analysis
system of the present invention. Using pattern recognition
algorithms, which may be discriminant functions, quantitative
features are continuously extracted from ongoing EEG data and used
to construct a scale for depth of anesthesia, the Depth Index (DI).
This information may be presented to the anesthesiologist to serve
as an adjunct to the manual management of the patient.
Alternatively, servo systems may be used to administer appropriate
agents automatically to control the DI.
[0016] The present invention presents a relatively simple and yet
effective and reliable system and method for the monitoring and/or
control of the multiple dimensions of anesthesia. The method is
based upon computation of the covariance matrix of spectral
quantitative EEG (QEEG) features within each electrode and among a
set of electrode positions. In its simplest form, it uses a set of
anterior (frontal) EEG electrodes on the forehead. When the patient
attains the surgical plane of anesthesia, the power in each band
will change within each electrode and the cross-spectral matrix
will change. One way to display this data may be as a scrolling
waterfall of the power spectra from each lead, updated at periodic
intervals (e.g., Compressed Spectral Array or "CSA"). The means and
standard deviations of baseline samples of the covariance matrices
and the measures may be used to define a self-norm. As updated
samples of EEG are analyzed, a comparison relative to population or
self-normative data is made of the absolute and relative EEG power
within each of the electrodes continuously or within selected
frequency bands, and the symmetry and coherence relationships among
these spectral measurements within and between the set of
electrodes. This comparison preferably entails transformation of
every measure for Gaussianity and rescaling the measure to the
common metric of probability by computing the standard or Z score
for each variable. A second way to display this data may be as a
scrolling waterfall of the Z-transformed spectra or ZSA. A third
way to display this QEEG data may be to extract selected,
differentially sensitive variables from the EEG and compute
separate composites such as Mahalanobis distances or discriminant
scores to provide scales which accurately assess DI, PI and MI.
[0017] These scores may be displayed as separate, updated numerical
values or as separate updated trajectories of the values versus
elapsed intra-operative or monitoring time. If the patient begins
regaining consciousness, sensitivity to pain or the ability to
comprehend speech and store memories, as shown by the trajectory
for the corresponding dimension, the confidence level (mean+2
standard deviations) around the self-norm (baseline) for that
dimension will be exceeded. An alarm may be sounded or a vibratory
signal transmitted. If that occurs, more agent, directed toward the
specific dimension displaying change of state, may then be
delivered (titrated) to the patient manually by the attending
medical personnel or, alternatively, the corresponding agent may be
automatically delivered via a self-adaptive servo algorithm.
Conversely, if these changes are excessive, less agent will be
indicated relative to the self-norm, and the attending personnel or
the servo system may reliably intervene to control the
administration of each of the agents in a manner optimized for the
individual patient.
[0018] The QEEG variables may be augmented by sensory evoked
potentials ("EPs") and autonomic data to obtain measurements for
quantifying the pain (PI) and memory (MI) indices. To obtain the
sensory EPs, the system presents to the patient a programmed
sequence of concurrent or sequential stimulations in one or
multiple sensory modalities. Preferably, two modes are used: (1)
auditory stimulation (e.g., auditory clicks or rectangular tone
pips at about 65 dB, modulated at a frequency selected to maximize
EP amplitude, such as, approximately 1500 Hz), delivered to the
ears via air tubes from an audio source at an `auditory tracer`
repetition rate F1; and (2) somatosensory stimulation consisting of
electrical shocks (e.g., 0.2 msec pulses of constant current at
about 12 mA delivered to a peripheral nerve, preferably via a
finger cot, at a second `somatosensory tracer` rate (F2). The
tracer rates F1 and F2, although concurrent, may preferably be
selected at different prime number frequencies to permit separation
of the different EP's and avoid interference. Concurrent
stimulations permit a more rapid, examination and provide the
patient's responses more quickly. However, intermittent sequential
stimulation may be more effective as habituation may readily be
avoided by randomizing sequences or other maneuvers to maximize EP
amplitudes. Based on the responses to the auditory stimuli, the
system tests the functional state of the lateral lemniscal auditory
pathway in the brain stem (Brain Stem Auditory Evoked Response or
BAER), the thalamus (Mid-Latency Auditory Evoked Response or MLAER)
and the auditory cortex ("AER"). Based on the responses to
electrical stimuli, the system tests the functional state of the
spinal cord, medial lemniscal pathways in the brain stem and the
somatosensory cortex (Somatosensory Evoked Response, or SER).
[0019] One way to quantify the EPs is to utilize separate tracer
frequencies, F1 and F2, in order detect the different times of
presentation of the stimuli in the two different modalities to
provide `trigger pulses` needed to compute the wave shape of each
of the average evoked responses in the time domain, using the
conventional evoked response averaging techniques. This selective
averaging may be performed whether the stimuli are presented
simultaneously or sequentially. The raw wave shapes may be
optionally displayed as a scrolling waterfall, or Compressed Evoked
Potential Array (CEPA). The system may extract from each such wave
shape a numerical feature of merit or a metric (e.g., such as the
length of the curvilinear outline or the area under the EP wave
shape). From a baseline sample for both the AEPs and SEPs, the mean
and standard deviation of the distribution of such EP measures may
be specified. Subsequent samples may be Z-transformed to provide a
common metric of probability. These Z-scores may be displayed as
periodically updating numerical values or as continuously updating
trajectories. They may also be combined with the Z-scores of the
separate QEEG measures found to be sensitive to pain or memory
storage into a `State Vector` in order to provide a multi-modal and
more sensitive and specific assessment. Such multivariate vectors
may be computed as the square root of the sum of the squared
separate Z-scores. Such vectors may combine QEEG and SEP Z-scores
to yield a Pain State Vector, QEEG and AEP Z-scores to yield a
Memory State Vector, or QEEG, SEP and AEP Z-scores to yield a Brain
State Vector.
[0020] Another way to quantify the EPs is to perform very narrow
band (e.g., using 0.5 Hz frequency bins) FFTs on the EEG recorded
in the absence of the tracer stimuli and during intermittent or
constant periods of stimulation. Using the very narrow band power
computed over a sliding window of appropriate length (e.g., 20 to
60 seconds), the power in the bin corresponding to F1 or F2 is
divided by the mean power of the two adjacent bins of lower
frequencies and the two adjacent bins of higher frequencies. The
power of the EEG is equal to its variance because the variance of a
set of samples of a variable equals the mean squared value minus
the square of the mean value across the set and the mean value of
the EEG is zero. Thus, this quotient of powers is equivalent to an
F-ratio. In this way, without actually computing an average
response wave shape, a statistically interpretable FIGURE of merit
can be readily provided for the responsiveness of the patient to
somatosensory or auditory stimulation. By constructing a database
of such F values in a baseline sample, the updating F ratio's can
be Z-transformed to probability and processed for display on a
monitor or inputs to a servo controller just as the features
extracted from the EP wave shapes.
[0021] Measures of vital signs (e.g., heart rate, stroke volume,
blood pressure, respiration and temperature) may also be obtained
and monitored from the anesthesiology console. In addition, oxygen
saturation may be measured (e.g., using an NIR sensor such as
"INVOS".RTM. (In Vitro Optical Spectroscopy). A preferred
comprehensive system monitors the electrophysiology of the patient,
detecting changes in available measurements of such vital signs.
Any such data which becomes available may be treated the same way
in principal (i.e., a baseline sample may be collected to serve as
the reference state). The quantified feature(s) may then be
assembled into a baseline distribution sample. After transforms for
Gaussianity, if necessary, the mean and standard deviation of each
measure are calculated. Z-transformation of the raw measure values
now rescales them all in the common metric of probability. These
may now be presented on the screen as numerical values or displayed
as continuous updating trajectories as univariates or as
multivariate "vital sign vectors" combined by computing the square
root of the sum of the squared Z-scores. While a mathematically
more correct multivariate may require correction for
intercorrelations using the covariance among the set of measures,
the simple square root of the sum of squares errs in the direction
of possible over-estimation of the vector length, which acts as a
`fail-safe` early warning signal. In particular, the normalized
variability in heart rate (HRV) has been reported to be a sensitive
autonomic indicator of pain. Z (HRV) might contribute enhanced
sensitivity if incorporated into the "pain vector" together with
the selected pain-sensitive QEEG variables and selected SEP
features.
[0022] As shown in FIG. 1, prior to a surgical operation, a
plurality of EEG electrodes (e.g., EEG electrodes 2a-2e) are
removably secured to the scalp 1 of the patient. Preferably, the
EEG electrodes will include the following forehead locations: F1,
F2, F7, F8 (all 4 active) and FPZ (reference). The capital letters
refer to position location names in the International 10/20
Electrode Placement System as would be understood by those of skill
in the art. Additional removable electrodes may be utilized as
desired while additional reference electrodes (unilateral or
linked) may be removably positioned on the patient's mastoids or
earlobes (A1, A2). An electrode may be placed on the shoulder over
Erb's Point to serve as confirmation that SEP are being conducted
through the spinal cord. EOG electrodes may optionally be placed at
the outer canthus of the eye to facilitate artifact rejection. As
would further be understood by those of skill in the art,
electrodes may also be placed on the central vertex (Cz) to record
brainstem potentials, on the chest for EKG recording and on the
cheekbone to serve as the ground.
[0023] The electrodes 2a-2e preferably use a standard electrolyte
gel, or other application method, for contact so that the
impedances of each electrode-skin contact are below 5000 ohms.
Alternatively, for some applications, needle electrodes, a
pre-gelled electrode appliance with adhesive or other means of
fixation, or an electrode cap or net with previously located
electrode positions may be used. The EEG system, described below,
automatically checks the electrode-skin impedance at each electrode
at frequent intervals, (e.g., every minute), and displays a warning
(e.g., a red LED light) if any such impedance falls below 5000
ohms.
[0024] As shown in FIG. 1, the patient's head 1 is connected to the
patient module which includes a desired number of electrodes 2a-2e.
FIG. 1 shows four active electrodes.
[0025] Each of the electrodes 2a-2e is connected to a respective
one of the EEG/EP amplifiers 3a-3e, with each electrode lead being
connected to its respective amplifier. Each amplifier 3a-3e has an
input isolation switch, (e.g., a photo-diode and LED coupler), to
prevent current leakage to the patient. The EEG amplifiers 3a-3e
are high-gain low-noise amplifiers, preferably having, for example,
peak-to-peak noise of 1 microvolt or less, a frequency range of 0.5
to 200 Hz, fixed gain of 10,000, common mode rejection of 100 db or
more (4 amplifiers). Two auditory or somatosensory brainstem EP
amplifiers may have, for example, a peak to peak noise of less than
1 microvolt, a frequency range from 30 to 5000 Hz, gain of 100,000
(2 amplifiers) and a common mode rejection of at least 100 dB.
Alternatively, high-gain amplifiers may be used with fixed gain of,
for example, 10,000 of which 2 may be remotely switched to a fixed
gain of, for example, 100,000. Amplifier parameters may be switched
for separate data collection of EEG and EP, separate amplifiers may
be connected to the same electrode input, or a programmable A/D
multiplexer converter may be used to output the separated data.
[0026] The amplifiers 3a-3e are connected to a four channel
analog-to-digital multiplexer 4 (A/D multiplexer). The multiplexer
4 samples the amplified analog brain waves at a rate of, for
example, 5 KHz for each channel. The multiplexer 4 is connected to
"buffer signal" 5 which stores the signal, and "buffer noise" 6
which stores samples of the "noise", that is, amplifier output of
EEG when no stimuli are delivered to elicit EPS. The buffers 5, 6
and A/D multiplexer 4 are connected to a dedicated digital signal
processor (DSP) 7, such as, for example, model TMS320C44.RTM.
(Texas Instruments). Alternatively, the DSP 7 may be a Pentium 4
Processor) (Intel) or a digital signal processor such as the
TMS320C44.RTM. (Texas Instruments) along with a microprocessor. The
DSP may be controlled by, for example, a software program 8 and
connected, through a dedicated 512-point FFT 9 (Fast Fourier
Transform) to a digital comb filter 10.
[0027] The comb filter 10 is connected to, and controls, the IFFT
11 (Inverse Fast Fourier Transform). The output of IFFT 11 is
connected to the system microprocessor 12. The microprocessor 12 is
also connected to, and controls, the stimulus generator 13 (e.g.,
lights, loudspeaker, shock, device, etc.), the mass storage 14
(e.g., a hard disk), the display 15 (e.g., a CRT), a printer 16 and
a keyboard operator control panel 17. The microprocessor 12
operates under control of a software program 18. Preferably, as
shown, the stimulus generator 13 is connected to "auditory" 20,
which generates clicks at, for example, 100 dB and at an "auditory
tracer" frequency "F1". The clicks may then be transmitted to the
patient via, for example, earphones or air tubes. The stimulus
generator 13 is also connected to "somatosensory" 21 which delivers
electrical stimulation (e.g., constant current electrical shock
pulses), for example, of 200 microseconds duration and 12 milliamps
current. The electrical stimulation may be transmitted to the
patient via, for example, a fingertip cot at a second, and
different, "somatosensory tracer" frequency "F2."
[0028] The digital comb filter 10 may be as described in U.S. Pat.
No. 4,705,049, incorporated by reference herein. The comb filter
may considered a series of band pass and band stop filters which
are responsive over a selected range. The selected range may for
example be is 0-3000 Hz and may, preferably be 0-1400 Hz.
Preferably, band pass filters may operate at 10-580 Hz, 600-640 Hz,
720-800 Hz and 900-1400 Hz with band-stop filters at 0-10 Hz,
580-600, 640-720 Hz, 800-900 Hz and above 1400 Hz. Thus the band
pass filters form the "teeth" of a comb and are selected to accord
with frequencies in which a signal/noise ratio is acceptable. The
band-stop filters are selected to remove frequencies in which the
noise is excessive.
[0029] The multiplexer 4 may be programmed to obtain samples of the
signal and of the noise. The "noise" is preferably obtained when
there is an absence of evoked potential stimuli and the "signal" is
obtained during stimulation, beginning with presentation of the
stimuli or after a pre-selected delay. The program 8 with its
controlled DSP 7 conditions the input signals and insures that they
are valid biological signals. Such validation checks on the input
signals include periodic calibration measurements and impedance
measurements and continuous automatic artifact rejection
algorithms. The microprocessor 12 automatically provides a timed
set of two kinds of stimuli for simulator 13: An audio sound from a
speaker or earphones and a tactile signal from the electric shock
of about 0.2 msec duration and about 12 mA of intensity delivered
to electrodes via the fingertip cot. Auditory clicks (e.g., about
100 db SPL) may be delivered through a stethoscope earpiece by air
conduction tubes from a magnetic speaker or other arrangement as
would be understood by those skilled in the art. Ideally, these
clicks may be rectangular pulses of 1500 Hz tones at a repetition
rate of about 40/sec. The rate of stimulus may range between
7-50/second and may more preferably range between 35-45/second
(i.e., eliciting a 40 Hz auditory steady-state evoked response (40
Hz) at an auditory tracer frequency 1 (F1)).
[0030] The patient's brain responds to these stimuli, providing
"Evoked Potentials" (EPs) which are averaged to reduce noise.
Sample size varies with stimulus modality, ranging from 100 (VEP)
to 512-2048 (BAER/BSER). The average EP is the sum of samples
time-locked to the onset of the stimuli divided by the number of
samples, to provide an updated average.
[0031] The software program provides patient information.
Typically, the patient header gives the patient's IDS number, age
and the date of the operation. In addition, it may contain the name
of the physician, anesthetist or other operator and the nature of
the procedure. The time is provided by a time code generator, which
records both local time and elapsed time directly on the EEG
tracings, so that events may be retrieved from any acquisition
session given input to the database of the date. Retrieved data
should include all clinical protocols and physiological
documentation, including the trajectories of the indices. The
software program provides the data analysis module, described in
detail elsewhere in this application.
[0032] After analysis of the data, the microprocessor 12 provides
information to the display 15 which informs the anesthesiologist or
medical personnel of the state of the patient with respect to the 3
dimensions being monitored. This data can then be used to guide
manual administration of agents in accordance with the clinical
judgment of the physician. Alternatively, this information may be
provided as control signals to a delivery control 19, which,
automatically controls three agent infusion pumps 22a-22c (e.g.,
Pumps A, B and C) to achieve a desired balance of the three agents.
If the anesthetic is gaseous, the anesthesia control 19 may control
valves of gas cylinders (not shown) as would be understood by those
of skill in the art.
[0033] Each of the three state indices (i.e., the DI, the MI and
the PI) are separately analyzed by the computer software of the
present invention, in the frequency domain and also in the time
domain.
[0034] The following is a preferred exemplary method for frequency
domain analysis of the depth of anesthesia to obtain the DI. The
frequency domain, from 0-200 Hz, is divided into narrow bins (e.g.,
for 0.50 Hz bins, 400 bins are set), QEEG variables are extracted
from 0.05-1.5 Hz (low delta) to gamma 2 (35-50 Hz). Based upon
experience (e.g., based on data from sets of prior patients),
features are selected from the data from univariate (i.e., single
electrode) and multi-variate (i.e., composite sets of electrodes)
measures.
[0035] The data, in the frequency domain, is preferably converted
by a Fast Fourier Transform (FFT) and then may be converted again
by an Inverse Fast Fourier Transform (IFFT). The FFT is the
preferred method for calculating a power spectrum of the patients'
brain waves. Using the Fourier transformation, the complex wave
diagram of the EEG is divided into underlying oscillation
components, followed by a translation from the time domain into the
frequency domain. The squared amplitudes of these oscillation
components form the "power spectrum." Further processing of the
results of the Fourier analysis may include the extraction of
spectrum parameters as well as continued statistical calculations.
IFFT may be performed after analysis of the relative phase
variances at each frequency, of segments containing EP signals and
segments containing only noise samples, removing noise by setting
appropriate coefficients to zero and reconstructing EPs with the
noise digitally removed. Parameters which may be derived from the
spectrum, include, for example, the total power and absolute and
relative power in different frequency bands. The median, the
spectral edge frequency, and the dominant frequency may also be
used as parameters. The median frequency is most often defined as
the 95% quantile (i.e., 95% of the total power of the spectrum is
below this frequency). The dominant frequency is the frequency with
the highest power. Mean powers within selected band intervals are
calculated, transformed to achieve a normal or Gaussian
distribution. Mean values and standard deviations of a baseline set
of samples of each QEEG or EP variable are obtained during an
adequate and appropriate reference period to define the patients
"self-norm." The relevant population norm is obtained (i.e., from a
look-up normative table). Z-scores are calculated for each
univariate or multi-variate QEEG or EP measure, relative to both
the self- and population-norms. For each variable, a sliding
window, for example, 20 seconds of data which is continuously
updated, is formed which integrates sequential segments (i.e., 2.5
second artifact-free EEG samples). From the updated mean value of
the sliding window, the trajectory of each variable and the DI, PI
and MI are calculated. The trajectory of each index is presented to
the physician as a quantitative monitor of each dimension of
patient state to provide guidance for the optimal management of the
patient or optionally may be used to automatically control the
delivery of various agents to the patient, preceded or accompanied
by display of the intended maneuver to the operator.
[0036] The EP wave shapes are stored. The peaks of the EPs are
detected and an EP Index ("EPI") is computed. The EPI reflects the
area under the EP curve, the length of the contour of the EP wave
shape ("string length"), its peak amplitudes and its latencies. An
updating EP waterfall type display may be computed (Compressed EP
Array, or CEPA), that scrolls (with time) with the EP peaks marked,
for example, as brightened points or by arrows or stars. The
automatic comb filter, mentioned above, may be used to define an
optimum digital filter for computation of any EPs. As in the case
of the BAER/AER, for all EPs, the data is stored, the peaks are
detected, and an EP Index ("EPI") is computed. The EPI reflects the
area under the EP, and its string length, peak amplitudes and
latencies. An updating scrolling waterfall display may be computed
and displayed (on the monitor) with the EP peaks marked. In
addition, separate updated sliding windows of data may be computed
and displayed (on the monitor) for the patient's vital signs.
Preferably, these vital signs include heart functions, as detected
by QRS peaks, heart rate variability, respiratory cycle, BP (Blood
Pressure), oxygen saturation, and temperature. These vital signs
windows are computed using the means value and standard deviation
for each of the vital signs.
[0037] The data collected and analyzed in the time domain and
frequency domain are used to form the patient's multiple indices.
These are, preferably, the Depth Index (PSI) (assesses anesthesia
level), the Memory Index (MI) and the Pain Index (PI). A preferred
method of computing these indices may be to use discriminant
analysis as described in U.S. Pat. No. 5,083,571 relating to
psychiatric classification of a patient with respect to a class or
specific disorder and the inventor's prior U.S. Pat. No. 6,016,444.
In general, discriminant analysis uses "discriminant functions".
U.S. Pat. Nos. 5,083,571 and 6,016,444 are hereby expressly
incorporated by reference in their entireties.
[0038] A discriminant function is composed of weighted combinations
of subsets of variables. In the case where patients' norms are
used, the subsets are Z scores. Each of the subsets (each Z score)
is selected, on the basis of experience and experimentation,
because it significantly contributes to the discrimination (e.g.,
discrimination between anesthetized and yet feeling pain and
anesthetized and not feeling pain). The weighting of the subsets,
the contribution of each Z score toward the discrimination, is also
based on experience and experimentation.
[0039] The distributions of features of two groups of subjects,
where the groups belong to different diagnostic categories, may be
thought of as two clouds of points in a multidimensional space in
which each dimension corresponds to a feature. For example, each
feature is a Z score and the diagnostic categories, for example,
are the degrees of anesthetization to prevent pain. There may be no
significant differences between two groups (i.e., significant
differences in other dimensions). A problem arises when these
clouds of points overlap, i.e., when there is no apparent
significant difference between two groups with respect to some
features. A solution is to attempt to define a boundary, through
the clouds of points, to create a first zone which includes as much
as practicable of the first group, and as little as possible of the
second group, and a second zone which includes as much as
practicable of the second group and as little as practicable of the
first group.
[0040] The third zone is defined as an overlap region where no
reliable classification can be made. In principle, a discriminant
function weights the values of selected features for a new patient
and adds these weighted values to specify a single point in the
relevant multidimensional space. This single point then would be in
one of the three zones, and the individual's category (in each of
the DI, MI and PI) would be classified accordingly. The
discriminant analysis is performed during the operation using Z
scores based on self-norms (i.e., comparison with the same patient
pre-operation) and population norms (i.e., patients of the same age
and condition during similar operations using the same anesthetic).
After the DI, MI and PI are computed, these computations may be
used to automatically administer the various anesthetics to the
patient. In addition, these indices are displayed to the operator
on, e.g., a monitor. They may also be recorded and printed out for
analysis after the operation. The DI gives an assessment in QEEG,
the depth of anesthesia, the Memory Index (MI) is obtained, in
QEEG, by combining the F (AER) value with selected AER features
(i.e., assessment of reception). This should give an indication of
the patients' ability to comprehend speech, i.e., the conversation
of the doctors and nurses during the operation. The Pain Index (PI)
is derived from the F (SER) values and selected SER features. In
addition, non-QEEG autonomic measures, which are responsive to
pain, may be used and computed into the PSI, PI and MI.
[0041] In order for the tendencies of the DI, MI and PI to control
and/or monitor the quantities of the various anesthetics, each of
which is primarily directed to one of those indices, it is
necessary to measure the effects of those anesthetics on the
individual patients. Population norms are based on gender, age,
surgical procedure and specific anesthetics. However, individuals,
due to their metabolisms and other factors, may react differently
from the average patient of such population norms.
[0042] The preferred method of determining the correct anesthesia
dosage for each patient is to test the patient using the 2 or 3
different anesthetic agents which will be used for the operation.
This QEEG method may analyze the particular patient's brain wave
reaction to each anesthetic agents, one at a time, and derive a
"transfer function" for each patient, reflecting that patient's
biochemical reactions to each anesthetic agent. For example, one
patient may require an injection of 5 milliliters of an anesthetic
agent to prevent a feeling of pain, as shown by his PI, while
another patient may require twice that dosage to obtain the same
effect. The transfer function is preferably updated at regular
intervals (i.e., for example every 20 minutes) during the
operation, as it may change if the operation lasts longer than
15-20 minutes.
[0043] A preferred method for calculating each of transfer function
may include perturbation analysis. After the patient has been
anesthetized to the desired plane of anesthesia, and his QEEG
self-norm (reference set-point) has been obtained, the system halts
delivery of the first anesthetic, for example, the anesthesia
remifentanyl primarily directed to control pain (PI) or may
diminish the delivered amount by some fraction, for example, 50
percent. The patient then starts, in a gradual way, to show a
change in the relevant index, e.g., DI, MI or PI. At a selected
distance from a set point, preferably about 2.5 Standard Deviations
(S.D.), (i.e., probability P<0.01), the application of the
particular anesthetic agent is resumed. The system, in this method
determines the number of anesthetic units withheld from the patient
to cause the change in the relevant index. For example, it may
require withholding 3 units for a particular patient to be roused
to 2.5 S.D. from the set-point of the PI. The amount of anesthetic
agent withheld, called the "test correction amount," is an
approximation of the amount of anesthetic agent required to restore
that particular patient to the selected index when he has deviated
from his set point by 2.5 S.D. A selected fraction of that amount
is then administered, as a first approximation, to see whether this
restores the patient to the set point. The amount required to
restore the patient to the set points is defined as the "correction
amount" and is retained in system memory and is administered to the
patient whenever the patient has deviated from his set-point by 2.5
S.D. or more.
[0044] Adequate determination of the transfer function may require
positive, as well as negative perturbations. Preferably, periodic
evaluation is shown by a significant change in each index (DI, MI
and PI) caused by a small increment in the amount of anesthetic
agent delivery, for example 10%.
[0045] As shown in FIG. 1, the anesthesia control 19, under
management of the microprocessor 12, controls the administration of
the different anesthetic agents. In this example, the anesthetic
agents are injections and they are administered intravenously by
infusion pumps A-C (22a-22c). For example, pump A (22a) may inject
propofol (to control DI), while pump B (22b) injects midzolam (to
control MI) and pump C (22c) injects remifentanyl (to control PI).
Alternatively, as would be understood by those of skill in the art,
any or all of the various anesthetic agents may be gases which are
administered through controlled inhalation by the patient.
[0046] For each index (DI, MI and PI), one infusion pump 22a-22c is
used to administer or withhold the anesthetic agent primarily
directed toward controlling that index. For example, the DI is
continually computed and compared to the desired value or desired
range of values. The pump (i.e., pump A (22a)) is energized (or not
energized) to inject (or withhold) the corresponding anesthetic
agent (e.g., propofol primarily to control the PSI). Similarly, the
MI and PI are continually computed and a corresponding one of the
pumps 22 (i.e., pump B (22b) or pump C (22c), respectively) is
controlled to inject, or withhold, the anesthetic agent primarily
directed to that index.
[0047] As would be understood by those of skill in the art, the
system of FIG. 1 may be implemented incorporating a dedicated
freestanding computer, such as a PC, a laptop or other handheld
device. Alternatively, the computer and monitor portions (as
distinct from the pumps) may be implemented as part of a
multi-modal monitor, which may also include sensors and displays of
the patient's vital signs (i.e., blood pressure, respiration, O2
saturation, temperature and pulse (heart rate)). In any event,
preferably, the display 15 is a monitor having a color screen to
display graphics and alphanumerics. The operator control 17 may
preferably include a standard ASCI key board which may be used to
enter the patient header (e.g., name, age, gender, hospital number,
date, medical procedure etc.) and comments (which may use function
keys). Preferably, the display shows the results of the QEEG
analysis continually during the operation. These displays may
preferably include:
a) The trajectories of each of the indices (DI, MI and PI)
separately either on the same screen or in sequence; b) The set
points and the selected ranges (permitted deviations) for each
index; c) The current numerical value for each index; d) A
waterfall type display or/and actual (raw data) brain waves
showing, for each data channel, the FFT, AER and SER; e) Coded
symbols and/or alarms for events which should be brought to the
attention of the operator, such as epileptic spikes, epileptic
seizures, burst suppression and abrupt changes in those vital signs
(e.g., BP, respiration, pulse (heart rate), 02 saturation and
temperature); and f) Wave shapes stored in an Epileptic form event
file (epileptic spikes and seizures) calculated and displayed as
well as their number and the their times of occurrences.
[0048] Other embodiments of the invention will be apparent to those
skilled in the art from consideration of the specification and
practice of the invention disclosed herein. It is intended that the
specification and examples be considered as exemplary only, with a
true scope and spirit of the invention being indicated by the
following claims.
* * * * *