U.S. patent application number 09/968454 was filed with the patent office on 2002-02-07 for axis shift analysis of electrocardiogram signal parameters especially applicable for multivector analysis by implantable medical devices, and use of same.
This patent application is currently assigned to Medtronic, Inc.. Invention is credited to Nelson, Shannon, Stadler, Robert W..
Application Number | 20020016548 09/968454 |
Document ID | / |
Family ID | 23072108 |
Filed Date | 2002-02-07 |
United States Patent
Application |
20020016548 |
Kind Code |
A1 |
Stadler, Robert W. ; et
al. |
February 7, 2002 |
Axis shift analysis of electrocardiogram signal parameters
especially applicable for multivector analysis by implantable
medical devices, and use of same
Abstract
We show how to determine whether there has been an axis shift in
an electrocardiogram waveform and how to use this for filtering out
bad electrocardiogram information and to modify an adaptive filter
that can be used to adapt the filtering of such electrocardiogram
information to make it available for determining physiologic
conditions even after an axis shift.
Inventors: |
Stadler, Robert W.;
(Shoreview, MN) ; Nelson, Shannon; (Stacy,
MN) |
Correspondence
Address: |
Beth L. McMahon
Medtronic, Inc., MS 301
7000 Central Avenue NE
Minneapolis
MN
55432
US
|
Assignee: |
Medtronic, Inc.
|
Family ID: |
23072108 |
Appl. No.: |
09/968454 |
Filed: |
October 1, 2001 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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09968454 |
Oct 1, 2001 |
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09280203 |
Mar 29, 1999 |
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6324421 |
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Current U.S.
Class: |
600/509 |
Current CPC
Class: |
A61B 5/341 20210101;
A61N 1/37 20130101; A61B 5/349 20210101; A61B 5/7203 20130101; Y10S
128/901 20130101 |
Class at
Publication: |
600/509 |
International
Class: |
A61B 005/04 |
Claims
What is claimed is:
1. A method for determining whether there has been an axis shift in
an electrocardiogram waveform comprising a repeated cycle of steps,
each cycle comprising the steps: a) for a given cardiac cycle,
collecting into a buffer selected characteristic portions of the
electrocardiogram signal and sampling specific point locations
within said portions based on measured values of said samples for
said portion collected, wherein a location corresponding to the one
of said samples that corresponds in time to a fiducial point
wherein said waveform, b) determining a selection of samples to
take from a cardiac cycle surrounding temporally said fiducial
point and from and based on values of electrocardiogram amplitude
of said samples producing a parameter representative of said a
cardiac cycle, c) determining if said parameter is out of a
predetermined range of said parameter, and d) declaring an axis
shift if said parameter is out of range for more than a
predetermined amount.
2. The method of claim 1 wherein said predetermined amount in step
d comprises a predetermined number of times out of a predetermined
number of cycles.
3. The method of claim 1 wherein said fiducial point is an R-peak
for said a cardiac cycle, and the following steps are used to
determine the R-peak point; finding a peak positive value and a
peak negative value in said buffer of samples, finding an
isoelectric sample, employing the amplitude value of said
isoelectric sample and said peak values to determine which of said
peak values is furthest from said isoelectric sample value,
declaring the sample with the peak value further from said
isoelectric sample value as the sample located at said R-wave
peak.
4. The method of claim 3 wherein in step "b" said parameter value
is an amplitude of an R-wave and is determined based on said R-wave
peak value.
5. The method as set forth in claim 1 wherein said declaration of
said parameter axis shift is used to determine ranges for
acceptable values for determining a physiologic characteristic from
the set of physiologic characteristics including T wave height
variation, ischemic condition or QT variation.
6. The method of any of claims 1-3 further comprising the step of
simultaneously performing steps a-d on a plurality of
electrocardiogram vectors, and still further comprising the step of
determining an axis shift combination value based on whether an
axis shift is declared for more than a predetermined number of
electrocardiogram vectors.
7. The method of any of claims 1-5 and further comprising the step
of adjusting an alarm threshold for a physiologic parameter change
based on whether an axis shift is declared.
8. The method of any of claims 1-5 further comprising the step of
adapting baseline values of said measured parameter to change
responsive to declaration of an axis shift.
9. The method of any of claims 1-5 further comprising the step of
adapting ST change variable filter coeficients responsive to
declaration of an axis shift.
10. The method of any of claims 1-5 further comprising the step of
adapting a noise filter to reduce sensitivity to motion artifacts
in a group of cardiac cycles surrounding the temporal location of a
declaration of an axis shift.
11. Apparatus for determining if an axis shift has occurred in an
electrocardiogram signal so as to provide a better data set for
evaluating a physiologic condition based on said cardiac
electrogram signal, wherein said apparatus receives said
electrocardiogram signal through a plurality of electrical leads
connected to provide said cardiac electrogram signal from a
plurality of electrical vectors, said apparatus comprising: an
electrogram reading device connected to said plurality of
electrodes for sensing the amplitude variation in the electrical
signal of a heart for each electrical vector, a sampling and
digitizing circuit for digitizing samples of said cardiac
electrical amplitude signal and to provide an output stream of
digitized sample point values representative of said samples, a
V-event detection circuit for generating a V-event signal at its
output indicating that a ventricular event has occurred, a buffer
circuit for holding a set of point values that are temporally
related to a time in a cardiac cycle when said V-event signal is
output from said V-event detection circuit, a fiducial point
determining circuit means for reading the set of point values from
said buffer circuit for determining which of said point values is a
fiducial point related to said V-event signal, a subset determining
and selecting circuit for determining based at least in part on a
temporal relative location of said determined fiducial point to
said set of point values which subset of said set of point values
to select and selecting them, a parameterizing processor circuit
for producing a set of parameter values related to said set of
point values selected and determined by said subset determining
circuit wherein at least some of the parameters produced are
evaluatable by a physiologic condition signal processor circuit, a
physiologic condition signal circuit means for calculating a
physiologic condition signal variable value, an expected range
value recalculating circuit for employing said set of parameter
values and said pre-calculated expected ranges to produce new
pre-calculated expected ranges to produce new pre-calculated
expected range values for a next set of parameter values to be
compared with a comparison circuit for comparing said
pre-calculated expected ranges with each parameter value from said
set of parameter values to determine if it is within its expected
range and producing a validity value and as output and for setting
an axis shift flag value as an additional output if said parameter
values exhibit axis shift characteristics, a cardiac cycle validity
determining circuit which recieves said validity value and said
axis shift flag values for determining if said validity value is
sufficient to employ said set of parameter values for determining a
physiologic condition and for recalculating said set of expected
ranges by said recalculating circuit and for providing a cycle
validity flag value signal representing the determination of
sufficiency of cycle validity for a cardiac cycle, an evaluation
circuit for evaluating said physiologic condition based on running
changes in said current physiologic condition variable value from
those cycles determined to be sufficiently valid.
12. Apparatus as set forth in claim 11 wherein said fiducial point
is an R peak.
13. Apparatus as set forth in claim 12 wherein said expected range
value recalculating circuit determines a value for said axis shift
flag based on a value of said R peak.
14. Apparatus as set forth in claim 11 wherein said sampling and
digitizing circuit comprises circuit means for sampling a plurality
of vectors of said electrogram signal simultaneously.
15. Apparatus as set forth in claim 13 wherein said parameterizing
processor circuit for producing a set of parameter values related
to said set of point values selected and determined by said subset
determining circuit produces a set of said parameter values for
each vectorl
16. Apparatus as set forth in claim 11 wherein said apparatus
further comprises a sealed and implantable housing having said
electrodes mounted thereon for use within a living body, and
further comprising a telemetry system for transmitting said
parameters outside said living body.
17. Apparatus as set forth in claim 11 further comprising alarm
threshold circuit means responsive to a predeteremined alarm value
for said physiologic condition signals to generate an alarm signal
if said apparatus determines a physiologic condition signal to have
reached said predetermined alarm value, and having adaptive
threshold setting circuit means for automatically adjusting said
predetermined alarm value based on a change in said axis shift flag
value.
18. Apparatus as set forth in claim 11 further comprising a noise
supression circuit means responsive to a change in said axis shift
flag value to adjust noise thresholds to allow for a larger range
of signal amplitude in the presence of a percieved axis shift.
19. Apparatus as set forth in claim 11 further comprising adaptive
filter circuit responsive to a change in said axis shift value for
adjusting said filter circuit to pass an adjusted range of said
physiologic condition signals to generate a secondary physiologic
condition signal based on said physiologic condition signals passed
through said adaptive filter circuit.
20. Apparatus as set forth in claim 11 further comprising adaptive
baseline value adjustment circuit responsive to a change in said
axis shift value for adjusting a baseline value of said physiologic
condition signal to produce a signal for enabling adjustment of a
drift filter parameter to accomodate axis shifts.
Description
CROSS REFERENCE TO RELATED PATENT APPLICATION
[0001] Reference is hereby made to commonly assigned co-pending
U.S. patent applications Ser. No. (P-7376) filed on even date
herewith for METHOD AND APPARATUS FOR FILTERING ELECTROCARDIOGRAM
(ECG) SIGNALS TO REMOVE BAD CYCLE INFORMATION AND FOR USE OF
PHYSIOLOGIC SIGNALS DETERMINED FROM SAID FILTERED ECG SIGNALS in
the names of Robert W. Stadler et al., Ser. No. (P-7001) filed on
even date herewith for IMPROVED METHOD FOR ISCHEMIA DETECTION AND
APPARATUS FOR USING SAME in the names Robert W. Stadler et al. Ser.
No. (P-8056) filed on even date herewith for DETERMINATION OF
ORIENTATION OF ELECTROCARDIOGRAM SIGNAL IN IMPLANTABLE MEDICAL
DEVICES in the names Robert W. Stadler et al.
FIELD OF THE INVENTION
[0002] This invention relates to a method and apparatus embodied in
an implantable medical device (IMD) or an external medical device
(EMD) for monitoring electrocardiogram signals and potentially for
finding myocardial ischemia of a patient's heart and optionally
applying a therapy to a patient experiencing ischemia.
BACKGROUND
[0003] Myocardial ischemia is the leading cause of morbidity and
mortality in developed countries. Myocardial ischemia involves
oxygen starvation of the myocardium, particularly in the bulky left
ventricular wall, that can lead to myocardial infarction and/or the
onset of malignant arrhythmias if the oxygen starvation is not
alleviated. Although myocardial ischemia is associated with the
symptom of angina pectoris, the majority of episodes of myocardial
ischemia are asymptomatic or "silent."
[0004] Accurate and rapid detection of myocardial ischemia is the
first essential step toward reducing morbidity and mortality from
this often silent but deadly condition. Without the knowledge of
the condition, it cannot be treated. A wide range of therapies are
known for the treatment of myocardial ischemia once it is detected,
including surgical revascularization, neural stimulation and a
variety of biologically active agents or compounds which can remove
blood clots, reduce cardiac workload or improve cardiac
circulation.
[0005] The electrocardiogram (ECG) or electrogram (EGM) of the
cardiac cycle detected across sense electrode pairs located on the
patient's skin or in the patient's body, respectively, is a
repetitive waveform characterized by a periodic PQRST electrical
activation sequence of the upper and lower heart chambers. The
PQRST sequence is associated with the sequential depolarization and
contraction of the atria followed by the depolarization and
contraction of the ventricles, and successive PQRST complexes are
separated by a baseline or isoelectric region. The PQRST electrical
activation sequence commences with the P-wave indicative of the
depolarization and contraction of the atria and is followed by the
QRS complex indicative of the depolarization and contraction of the
ventricles. The T-wave at the termination of the ST segment time
delay is associated with re-polarization of the ventricles. The
PQRST electrical activation sequence with intact A-V activation
detected across a sense electrode pair is fairly predictable in
shape. The P-wave, R-wave and T-wave events occurring in sequence
in the range of normal heart rates are usually readily recognized
by visual examination of the external ECG or an EGM recorded by
implanted electrodes that are correctly oriented with the
depolarization waves. The P-wave and R-wave are readily sensed by
sense amplifiers of a monitor or therapy delivery device coupled
with appropriately placed sense electrode pairs.
[0006] The ST segment of the ECG or EGM is typically close in
amplitude to the baseline or isoelectric amplitude of the signal
sensed between PQRST sequences, depending on the sense electrode
pair location. During episodes of myocardial ischemia, the ST
segment amplitude is elevated or depressed (depending on
positioning of the ECG or EGM sense electrodes in relation to the
heart) from baseline. These ST segment deviations can be readily
recognized by visual examination.
[0007] The physiological basis of ST segment deviation changes in
the presence of cardiac ischemia may be explained by ischemic
changes in the action potential of cardiac myocytes. When myocytes
become ischemic, the resting potential increases (toward zero), the
depolarization slope of the action potential decreases, the plateau
decreases in voltage, and the duration of the action potential
decreases. These changes result in voltage gradients and an "injury
current" between normal and ischemic myocardium during the resting
and plateau phases of the action potential. Because the voltage
gradient between the normal and ischemic myocardium is positive
during diastole and negative during systole, the isoelectric or
baseline signal level and the ST segment signal level of the ECG
are displaced in opposite directions during ischemia. The change in
the isoelectric or baseline level is not easily detected because
the pair of sense electrodes implanted in the patient's body are AC
coupled through filters to the inputs of differential sense
amplifiers. However, the disparity between the isoelectric or
baseline level and the ST segment may be detected if the
isoelectric or baseline point and the ST segment point can be
identified.
[0008] It has long been a goal in the development of external
cardiac monitors and IMDs to be able to automatically detect ST
segment Deviations from baseline and to accurately determine when
the heart is ischemic therefrom so that the patient's cardiac
condition can be assessed and treated both in the clinical setting
and while the patient is outside a clinical setting. A wide number
of implantable therapy delivery devices and/or monitors have been
proposed for detecting ischemia and delivering a therapy and/or
recording the detected ischemic events in an ambulatory patient.
Fundamentally, the algorithms employed in these systems endeavor to
automatically sample the amplitude of the ST segment in the PQRST
complex in an EGM or ECG signal, compare its absolute amplitude
against a threshold and declare an ischemic or normal condition
based on the results of the comparison.
[0009] In regard to Implantable Medical Devices (IMDs), commonly
assigned U.S. Pat. Nos. 5,199,428 and 5,330,507 and U.S. Pat. No.
5,203,326, are incorporated herein by reference, and describe the
historical development of electrical stimulation of the carotid and
vagus nerves and other nerves to relieve cardiac arrhythmias and
angina pectoris associated with myocardial ischemia. Perhaps more
important to the background of this invention, they also describe
relatively simplistic methods for detecting cardiac ischemia. The
'326 patent also proposes providing backup anti-tachyarrhythmia
pacing and cardioversion/defibrillation shock therapies. U.S. Pat.
Nos. 5,531,768, 5,497,780, 5,135,004 and 5,313,953, all
incorporated herein by this reference, monitor or detect myocardial
ischemia and some record data related to ischemic episodes for
telemetry out at a later time, to provide therapy or even to set
off an alarm.
[0010] In these ischemia detection IMDs, the ischemia detection
depends entirely or at least in part on the location of a fiducial
point in the PQRST sequence, sampling the EGM signal level at a
point within the ST segment in the PQRST sequence, and detection an
elevated or depressed ST level exceeding a threshold level.
Automatic detection techniques are set forth in the
above-incorporated '428 and '507 patents that depend on sensing the
R-wave, setting an ST segment time window timed from the detected
R-wave, sampling the amplitude and/or integrating the amplitude to
develop a current event ST signal level, and comparing the current
event ST signal level to a threshold signal level that is derived
from an average normal ST signal level. In the '953 patent, a
computationally expensive template establishing and matching
algorithm is set forth that determines "I" and "j" deflection
points preceding and following the R-wave of each PQRST sequence as
the fiducial point or points. The ST segment signal level is
sampled 80 ms after the determined "j" point and is compared to the
threshold signal level.
[0011] In the above-incorporated '428 patent, it was proposed that
the detection of myocardial ischemia be accomplished by also
sensing the patient's coronary sinus blood pH and/or oxygen
saturation and comparing each to preset, normal thresholds. The
sensors are located in the coronary sinus or a coronary vein to
measure the dissolved oxygen and/or the lactic acid level of
myocardial venous return blood. The system includes programmable
thresholds against which the signals developed by the sensors and
the ST segment deviation are compared. When ischemia is confirmed,
the disclosed system triggered burst stimulation of selected nerves
until the blood gas and/or ST segment variations returned to
non-clinical risk levels. However, blood oxygen sensors that
perform adequately over a period of chronic implantation have not
been perfected, and blood oxygen changes can be due to conditions
or physiologic states of the patient other than ischemia.
[0012] These prior approaches are also problematic for a number of
reasons that contribute to the magnification of the deviation of
the sampled ST signal level from the isoelectric level due to
factors and conditions other than myocardial ischemia, thus
registering too many false positive indications of ischemia to be
very useful. Myocardial ischemia can be mistakenly detected due to
ST segment changes in the PQRST complex caused by "axis shifts",
electrical noise, cardiac pacing, and high sinus or tachycardia
cardiac rates that distort the shape of the PQRST complex. These
problems are described, for example, in "Analysis of Transient ST
Segment Changes During Ambulatory Monitoring" by Franc Jager et al.
at Computers in Cardiology, 1991, Los Alamitos: (IEEE Computer
Society Press 1991; 453-456), "An Approach to Intelligent Ischemia
Monitoring" by Bosniak et al. in Med. and Bio. Eng & Comp,
1995, pp. 749-756, and in "A Compact, Microprocessor-Based
ST-Segment Analyzer for the Operating Room" by Seven J. Weisner et
al., (IEEE Trans. on Biomedical Engineering BME-29, No.
9:642-648.
[0013] For detection of axis shifts and eliminating their
confounding effects on attempts to establish a reliable ischemia
detection system, the Jager algorithm (from his article listed in
the preceding paragraph) measures the electrical axis angle and the
difference between the ST segment and the isoelectric level over
two periods, one immediately after the other, and compares the
difference in mean the parameters between these two periods to a
threshold. Bosniak et al. use a multistate Kalman filter to look
for step changes in ST segment, representing axis shifts. This
method is far too complex for current generation implantable
devices.
[0014] There remains a need for a system capable of automatically
and reliably detecting ischemia. Significant advantage can be had
if it is able to detect ischemia in any portion of the patient's
heart. Ease of implantation, stability and long term use in
ambulatory patients is obviously a consideration. Important also is
that such a system reliably and consistently distinguish ischemia
from other conditions or physiologic states of the patient.
Additionally an indication of the location of the ischemia is
useful too.
[0015] This can be characterized as a need for such a system for
accurately detecting myocardial ischemia through measurements of
the cardiac EGM in more than one sensing axis to account for the
possible locations of ischemic regions of the heart that is easily
implanted and functions reliably over time, even as the heart
condition changes.
SUMMARY OF THE INVENTION
[0016] The present invention provides apparatus requirements and
algorithmic processes that can be used to satisfy some or all of
these needs. It contemplates a more reliable and consistent method
and apparatus implementing an algorithm in an IMD which may also be
useful for an external medical device for automatically and
accurately detecting myocardial ischemia and triggering delivery of
a therapy, data storage, and/or diagnostic assistance, as well as
processing abilities to filter out bad data from electrocardiogram
signals for other purposes as detailed and described within. It is
also useful to find which cardiac cycles might have data which
would be invalid for one purpose but which would therefore be
indicative of a changing physiologic condition. Accordingly,
filtering out the "bad cycle" information can yeild useful
indicator data as well from the information contained in what would
otherwise be considered invalid cycles.
[0017] It is thus an object of the present invention to accurately
detect episodes of myocardial ischemia from sense electrodes
located on the patient's skin or in the patient's body and
distinguishing ST segment deviations due to ischemia from ST
segment deviations that may be caused by one or more factors other
than actual ischemia, including at least electrical noise, "axis
shift", cardiac pacing, and distortion of the PQRST complex due to
arrhythmias and high sinus heart rates.
[0018] It is a further object of the present invention to
accurately detect episodes of myocardial ischemia in this manner
from sense electrodes arranged to provide a plurality of sense
electrode pair vectors for developing a plurality of vector ECG or
EGM signals from substantially the entire heart where ischemia
develops.
[0019] The collection of electrogram data includes samples taken
from portions of the cardiac cycle including portions in a QRS
complex, (usually to find the R-wave peak, although this is not
necessary in some embodiments); and samples in the ST segment: plus
at least a sample in an isoelectric area, usually prior to the QRS
complex, although following the T-wave would be acceptable also for
finding an isoelectric point for the processes we describe.
[0020] At least one or more of the objects are realized in a system
providing, in general and preferably, at least one of the following
features.
[0021] Adaptive noise detection, (i.e., the device will enable
parameterizing the waveform, comparing current parameters to
expected ranges, updating expected ranges from the current waveform
if the majority of parameters are within range, and keeping track
of the frequency with which a parameter does not fall within the
expected range to adapt to abrupt rhythm changes). With these
processes, an algorithm in the apparatus can adapt to accept the
heart rhythm of any individual and exclude cardiac cycles that do
not fit the normal pattern for such an individual. Our noise
detection algorithm is free of thresholds except the number of
cycles out of range that constitutes a rhythm change (this is 12 in
the most preferred form of the algorithm).
[0022] An additional novel feature of the noise detection is its
ability to take advantage of multiple, preferably orthogonal,
vectors. In other words, rather than check if a parameter is
outside of a 1-D allowed range, using our invention we can check if
a vector parameter is outside of a multi-dimensional "allowed
space".
[0023] Adaptation to slow changes in the rhythm of the individual
by adjustments to variables we maintain in memory with values for
the expected ranges of parameters, and eventual acceptance of
abrupt changes in rhythm by automatic broadening of expected
ranges.
[0024] We have also provided a feature designed to make the signal
indifferent to AC noise (typically 50 or 60 Hz) in the ECG signals,
because this is the most common frequency of noise in the modern
world. In preferred embodiments we set the ECG sample rate at an
integer multiple of 50 or 60 Hz and average all ECG measurements
over complete cycles of 50 or 60 Hz. Therefore, by sampling at
twice the AC frequency, and averaging all measurements over two
samples (thus producing a frequency domain "zero" at the AC
frequency)we essentially eliminate the power frequency noise. This
feature may have separable applicability to monitoring body signals
generally.
[0025] Also, it may be noted that the ST segment measurements are
conducted at multiple locations based on rate-adaptive delays from
the peak of the R-wave. Therefore, at higher heart rates, the
location of the ST measurement is closer to the QRS complex.
[0026] Most algorithms base ST segment location on delay from the J
point. The J point is difficult to locate algorithmically. The
difficulty results in variation in the actual location of
measurements. Use of the peak of the R-wave temporal location for
finding the places to measure the electrogram signal gives our
approach an unusual starting point.
[0027] Adaptations to use the invnetion during pacing are also
described.
[0028] Preferably, too, the measured ST changes are filtered so
that only ST changes that occur at rates that are characteristic of
human ischemia are accepted. Since commercial algorithms look at
absolute ST deviation, they have trouble with ischemic ST
deviations that are superimposed on slow ST drift. Commercial
algorithms usually have some filter to exclude the fast "noisy" ST
changes, but not to remove the slow drift. Our filters get rid of
both slow and fast ST deviations. The result of our algorithm is a
"relative" ST deviation as opposed to an absolute measurement of
deviation. Our filters respond to ST changes at physiologic rates
(measured empirically), and reject all changes outside this range
as noise.
[0029] Observation of ST segment changes can take advantage of
orthogonal ECG leads with our apparatus. The difference between the
ST segment and the isoelectric level can be treated as a
3-dimensional vector, whose position is determined by 3 orthogonal
ECG leads. (One could use our teachings for 2- and n-dimensional
vectorization of the ST segment variation constraints as well). The
temporal evolution of the ST vector is tracked over time for
movements that are representative of ischemic changes. This
improves the sensitivity of the device, and combines ECG leads so
separate processing of each lead vector can be eliminated. This is
similar to multidimensional noise detection described earlier in
this summary, except that here the orthogonality is applied to the
"signal" (i.e., the ST change), not the noise. For example, is the
ST change vector moving away in space from it's expected location?
At what velocity is it moving? Is this movement indicative of
ischemia? If the changes are too slow or too fast they will be
ignored in preferred embodiments.
[0030] Another preferred feature is the detection of axis shifts
and removal of their potential confounding effects on ST segment
observations. This provides an additional basis for determining
good ischemia signals in ST segment analysis for ischemia, and thus
good ischemia detection results. Particularly when using the other
inventive analysis described herein. Axis shifts occur when
postural changes (of the patient) alter the location of the heart
with respect to the recording electrodes. They can cause sudden and
significant changes in the ST level. We describe how to detect axis
shifts by establishing expected ranges for the amplitude of the
R-waves in each vector, and declaring an axis shift if the measured
R-wave amplitude consistently falls outside of the expected
range.
[0031] In another preferred feature, we normalize the measured ST
deviations from the isoelectric point by the R-wave amplitude.
Traditionally, ST deviations are measured in micro-volts (or
millimeters on a standard strip chart). 100 micro-volts deviation
of the ST segment is considered to be significant in the art of
external (surface) ST segment deviation measurements. For an
implanted device, the amplitudes of the ECG or EGM are quite
different than surface ECG amplitudes. Rather than calibrate each
patient's device to absolute voltage units, and derive some new
significance threshold for ST changes in an implanted device, our
approach has been to prefer normalization of the ST change by the
R-wave amplitude makes common thresholds (i.e., 10%) applicable to
all patients. (This has a multidimensional aspect as well, as the
R-wave amplitude and ST deviation can be vectors, and the vector
deviation of the ST segment form the isoelectric baseline can be
normalized by the magnitude of the R-wave).
[0032] We also prefer to look for a positive and a negative peak
after sensing that we have found an R-wave. We then compare them
and choose the larger absolute valued one as the R-peak. To reduce
cost or complexity, this feature may only used during setup to
account for polarity switching, and then once the orientation of
the R-wave is known, the first or second peak may always be chosen
as the R-peak sample. It is preferrable to periodically or
continually check employ this feature to be sure there is not a
change in direction, however.
[0033] In another preferred feature, we provide detection of
ischemia in the presence of paced ventricular rhythm. If the rhythm
includes ventricular pacing the QRST morphology is distorted and
standard measurements of ST segment are inaccurate for detection of
ischemia. In the present invention, sporadic ventricular pacing is
ignored and ST measurements are conducted (i.e., the signal is
sampled) only on intrinsic beats. In the presence of consistent
ventricular pacing, ischemia is detected by temporarily modifying
the pacing rate (if possible) to let the ST measurements be
obtained at a consistent paced rate. For example, for every minute
of paced ventricular rhythm, the pacing rate would be set to 70 bpm
for a period of for example, 3 beats. The ST segment and
isoelectric segment measurements can them be made at these same
rate paced beats. This could be done about once each minute. For
the algorithm discussed within, the average R-R interval would be
that of the 3 paced beat rate.
[0034] An alternative for using the other features of this
invention during pacing is to use consistent pacing timing but
adopt the pacing spike as the fiducial point and the times of
measurement of the ST segment will then be at a constant delay from
the delivery of the pacing stimulus. In other words, substitute the
pacing pulse for the R-wave peak for the rest of the decisions.
BRIEF DESCRIPTION OF THE DRAWINGS
[0035] The present invention is described with reference to the
following drawings, in which like parts may be denoted with like
numbers, and wherein:
[0036] FIG. 1A is a diagrammatic illustration of the heart its
associated blood vessels and nerves, and a monitor or therapy
delivery IMD of one embodiment of the present invention coupled
thereto, and also illustrating an external device for communicating
with the IMD;
[0037] FIG. 1B is an illustration of an alternative form of an IMD
for use with this invention.
[0038] FIG. 1C is an illustration of an external system for use
with this invention.
[0039] FIG. 1D is an illustration of an alternative arrangement
using defibrillator electrodes and the cardiodefibrilation housing
for the electrode array in accord with other preferred
embodiments.
[0040] FIG. 2 is a simplified block diagram of an Implantable
Medical Device (IMD) system for embodying the present
invention;
[0041] FIG. 3 is a circuit block diagram illustrating the
implementation of several features and parts of preferred
embodiments
[0042] FIG. 4 is a graph of an EGM waveform of an exemplary cardiac
cycle illustrating a non-ischemic ST segment deviation and sample
points employed in the ST segment processing algorithm of a
preferred embodiment of the invention;
[0043] FIG. 5 is a graph of an EGM waveform of an exemplary cardiac
cycle illustrating an ischemic ST segment deviation and sample
points employed in the ST segment processing algorithm of a
preferred embodiment of the invention;
[0044] FIG. 6 is a block diagram showing a generalized set of steps
employed in a preferred embodiment of the invention.
[0045] FIGS. 6, 7, and 9-16 are a flow chart illustrating the steps
of performing the ischemia detection method of the present
invention from the plurality of EGM signal data point sets.
[0046] FIGS. 8A-C are diagrams of a 60 Hz noise waveform.
[0047] FIGS. 17-19 are graphs.
[0048] FIG. 20 is a drawing of a three dimensional graph of
multiple sensor vectors and a region definable with respect to
them.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS OF THE
INVENTION
[0049] The process in general and device/body configurations
[0050] The process of finding the signals that indicate the
presence or absence of ischemia taught in this invention is not
straightforward, but with reference to FIG. 6, the generalized
process steps 1-7 of the process 9, are laid out simply. More than
one set of procedures can be combined to complete all the steps
laid out in FIG. 6, or they can all be done together. Thus it can
be considered a plurality of inventions, since some of these
processes could be used with different devices and for different
purposes. Thus, one could filter out troublesome cardiac cycle
signals for purposes of providing good data for other diagnostic
purposes than ischemia detection, and one could employ the ischemia
detection processes without some of the enhanced processing
provided by excluding bad cardiac cycles, for example. Further, the
use of the ischemia parameters defined by these inventive processes
provides the basis for closed loop therapeutic intervention.
[0051] Referring to step 1 of FIG. 6, on each cardiac cycle, the
buffers are filled with signal samples. A basic filter may be used
to get rid of drift and high frequency noise. Then characteristic
features of the electrocardiogram waveform are picked out in step
2. The waveform is parameterized and a complex set of noise
detection steps are applied in block 3 (steps S140-S159 and similar
numbers on other blocks refer to detailed process steps explained
later with reference to more detailed figures). The signal values
are then checked for axis shift in block 4. Then a range valuation
is made to see if the parameters fit within expected ranges in
block 5. At this point an ischemia parameter value can be
calculated and compared with a programmed threshold in block 6.
With the evaluation of this ischemia parameter, the medical device
can provide what we call closed loop functions, such as neural
stimulation, release of medicaments or drugs, changes in electrical
stimulation of the heart, setting of alarms and so forth, and of
course recording the data for diagnostic and physician usage. These
are called closed loop because it means the medical device, with or
without intervention by a physician or patient, can adjust to the
ischemic condition, and possibly even relieve it, once it has made
a determination that it exists.
[0052] Of course the preferred form of device to do this would be
implantable, allowing the patient to continue with normal life
activities while this closed loop activity occurs. External devices
can use this invention also, however. Additionally, use of the
filter parameters discussed herein will enable a medical device to
find changes in cardiac rhythm that may be useful for cardioverter
defibrillator response to indicated changes in patient
condition.
[0053] It is generally desired that trauma be avoided as much as
possible in the implantation of cardiac therapy delivery and
monitoring IMDs including their associated leads and electrodes.
Thus, minimally invasive procedures are employed that typically
involve transvenous implantation of EGM sensing and therapy
delivery leads into the patient's right heart chambers or cardiac
vessels accessed from the right atrium when combined with a
pacemaker or an implantable cardiodefibrillator or just whenever
the right ventricular lead would be felt useful. The right
ventricular electrode is typically lodged deep into the apex of the
right ventricle, and a return electrode is located either on the
same ventricular lead for bipolar ventricular EGM sensing or on the
IMD housing for unipolar ventricular EGM sensing. The use of just a
single electrode pair to derive a single EGM signal for processing
to determine if ST segment deviation exists does not necessarily
provide enough information to accurately detect ischemia under all
conditions and locations of the ischemic area of the heart in
relation to the sensing vector of the electrode pair. In some
preferred embodiments we may use a number of electrodes on the
surface of the IMD itself, or a number of stub or other leads that
may be tunneled around the patient's body to provide an expanded
set of electrode pairs from which to extract the optimum range of
signals and thus have the best opportunity to detect hidden
ischemic conditions.
[0054] Electrode configurations in general
[0055] In one preferable embodiment an IMD having a plurality,
preferably three, EGM sense electrode pairs that are aligned as
much as possible with the three axes of the body but it is not
necessary that they pass through the heart, although that can
provide acceptable ischemia detection resolution. Typical IMDs are
shaped to have relatively flat and thin profiles so that they can
be implanted subcutaneously in frontal locations of the upper
thoracic regions or the lower abdominal region and remain
inconspicuous. Tunneling a lead around the patient's back is a
variation too. Without the electrode at the patient's back, the
leads tend to provide electrode configurations yielding signals
from the Coronal plane defined by the Superior-Inferior (S-I) and
Lateral-Medial (L-M) body axes, although, in practice, the plane
may be tilted somewhat into the Anterior-Posterior (A-P) body axis
also. In FIG. 1A, the IMD sensing axes S-I and L-M are drawn
through the IMD 30, and as would be apparent from relating this to
common anatomical references, the A-P axis for sensing is at a
right angle to both the S-I and L-M axes, extending from the front
major surface to the rear major surface of the patient's body. The
sense electrode pairs can take a wide variety of forms, and only
one exemplary form is illustrated in FIG. 1A. Three EGM signals
from the three respective electrode pairs that are preferably
arranged orthogonally to the extent possible are processed in
parallel in accordance with the algorithm of the present invention
described below. FIG. 1B illustrates an alternative embodiment 11
with 5 electrodes A-E, three located on the surface of the can
itself (B, D, and C) and one in the connector block 15 (that is,
electrode A), and one for the front of the patient body or in the
patient's heart, electrode E and another electrode F, for being
tunneled to the patient's back, both F and E being at the far ends
of lead extensions 17 and 19 from lead L.
[0056] Also illustrated in FIG. 1A, is a communications device or
programmer 13, for communicating with the IMD through the patient's
body B and/or the air, any data transfer that would be useful for
fully utilizing the information available to the patient or
physician now with the use of this ischemia detection system herein
described. Thus an antenna 57 would communicate with the telemetry
circuits (see FIG. 2) when required. A display 59 would enable
graphic and textual interface with the physician or patient, and a
series of buttons could provide for activation of commonly used or
emergency type functions. A speaker/microphone (not shown) could
provide for aural communications as well, such as an alarm or voice
recognition.
[0057] FIG. 1C provides an illustration of a patient P with a
system in accord with the instant invention used implemented
entirely with an external device 19, having a set of electrogram
electrodes A-F positioned about the patient's body.
[0058] FIG. 1D prodices a sense for how the teachings of this
invention may be employed in a defibrillation device. In the system
300, the cardiodefibrillator and or pacemaker 301 can employ the
outer housing 304 as an electrode, and it may be additionally
provided with point electrodes 306, 307, 308 at various locations
on the housing or the connector block 305. The typical device also
has leads 302 and 303, for providing defibrillation coil electrodes
310 and 309 in two chambers. These leads may contain additional
electrodes at points like 311, 312, 313, and 314, for examples. All
of the lead electrodes, including the coils may be used to provide
one electrode for a vector, and the best available vectors for use
with this invention in such systems will most likely be between a
lead elecctrode and one on the device 301.
[0059] Referring back to FIG. 1A, the IMD 30 is formed in the
typical manner of a hermetically sealed housing 32 having a
connector block assembly 34 attached to the housing 32 for
receiving one or more proximal connector ends of one or more
cardiac lead, e.g., ventricular endocardial lead 40, in this case.
In this embodiment, the IMD 30 is also formed with an orthogonal
Subcutaneous Electrode Array (SEA) of the type described in
commonly assigned U.S. Pat. No. 5,331,966, incorporated herein by
reference, or described in the above-referenced '953 patent.
[0060] The SEA electrodes comprise the four small surface area
electrodes 54, 56, 58 and 60 that are mounted to the peripheral
edge of the non-conductive connector block assembly 34 and the side
and bottom of the housing 32 orthogonally to one another and in a
planar spatial array and the two front and back electrodes 52 and
50 mounted to the planar major surfaces of the housing 32. These
electrodes 50, 52, 54, 56, 58 and 60 are mounted to an insulating
substrate that insulates them from one another and from the
conductive housing 32. Feedthroughs (not shown) are employed
through the peripheral edges and/or sides of the housing 32 to make
electrical connection between the electrodes 50-60 and circuits
within the housing 32 described below.
[0061] The IMD 30 is intended to be implanted subcutaneously in the
patient's torso at a distance from the heart 10 such that the SEA
electrodes are not in direct contact with the heart. The circuitry
within IMD 30 includes three differential sense amplifiers that are
selectively coupled with SEA electrode pairs in a manner to be
described below such that the one-dimensional sensing axes of the
three selected electrode pairs are at least physically mutually
orthogonal. While the SEA electrodes 50-60 can be selected in sense
electrode pairs that do have true orthogonal alignment, fewer SEA
electrodes can be alternatively located about the IMD housing.
Moreover, as described below, one of the electrode pairs can
include a sensing electrode or electrodes located on the lead 40.
In such alternative configurations, the sensing axis of at least
one of the electrode pairs is angularly offset and not truly in
mutual orthogonal relation with the sensing axes of the other two
electrode pairs. The offset angle can be compensated for by biasing
the EGM signal derived from it in a manner well known in the
art.
[0062] For convenience, the sensing axes of the selected electrode
pairs are referred to in the following description as the S-I, L-M
and A-P sensing axes, although the IMD 30 is likely to be implanted
such that they are not in true alignment with the corresponding
body axes of the patient. In addition, the term "lead vector" is
used herein as designating the EGM signal derived along the sensing
axis of each selected are nominally designated the L-M, S-I and A-P
vector signals or lead vectors as described further below.
[0063] It will also be understood from the following description
that these lead vectors can be combined mathematically to derive a
single or multi-dimensional "spatial vector" or a set of single or
multi-dimensional spatial vectors from selected pairs of the three
lead vectors. In the algorithm described below, the two or three
dimensional spatial vector can be advantageously formed from the
two or three lead vectors and processed as described. However, for
convenience, the algorithm is described employing parallel
processing of the three lead vectors with examples provided for
alternatively processing spatial vectors.
[0064] It will be further understood that the algorithm can also be
advantageously employed to process only a single lead vector or two
lead vectors or the spatial vector derived therefrom to determine
the presence or absence of ischemia. The use of all three lead
vectors or spatial vectors derived therefrom provides a higher
accuracy in the determination of the occurrence of an ischemic
episode.
[0065] Continuing in reference to FIG. 1A, the three lead vectors
generated by the three sense amplifiers are sampled and digitized
in parallel to derive a plurality of ST segment sampled data point
levels that are employed in an ischemia detection algorithm of the
present invention for determining the onset and continuation of an
ischemic episode. In one preferred programmable embodiment, one of
the sense electrodes 50-60 is not used. However it is reasonable to
use all six electrodes or to use 5 with one extra for redundancy,
or a subset thereof to eliminate some for lack of good signal, as
desirable given the circumstances which will become clear as this
explanation proceeds. It is contemplated that the sets of sense
electrodes that are used can be selectively programmed at implant
to provide the best set of three axis EGM signals. The selection
can be changed later by reprogramming to account for rotation or
movement of the IMD 30 in the subcutaneous implantation pocket
after implantation. Of course, the IMD 30 can be manufactured with
a selected set of such sense electrodes and without the sense
electrode programming capability.
[0066] To provide for the opportunity to have orthogonal sensing
axes, the sense electrodes 50, 52, 54 and 58 are arranged in a
nominal S-I sensing axis, and the sense electrodes 50, 52, 56 and
60 are arranged in a nominal L-M sensing axis, assuming that the
IMD is implanted in the depicted orientation with respect to the
patient's thoracic body axes. It must be recognized that this
invention will operate with any set of electrode pairs, even if the
vectors they represent are not truly orthogonal. It is simply
easier to think of these vectors as orthogonal, and orthogonality
is preferred, even though not required. Sense electrodes 54 and 58
are employed to define the nominal S-I sensing axis or lead vector.
Sense electrodes 56 and 60 are employed to define the nominal L-M
sensing axis or lead vector. The sense electrodes 50 and 52 or the
elongated, large surface area (coil) right ventricular sense
electrode 42 located on the lead 40 (or any electrode in that area)
may be employed to define the nominal A-P sensing axis or lead
vector. Any one of the unused sense electrodes can be employed as a
separate ground electrode for the three EGM axis sense amplifiers
and for an indifferent electrode in combination with the distal tip
electrode 44 of lead 40 for unipolar sensing of the R-wave. The
major surface sense electrodes 50 and 52 can be the same size or
differing sizes, wherein the larger major surface sense electrode
can be employed as a stimulation electrode in a pacemaker or
cardioverter/defibrillator therapy delivery IMD. Thus, FIG. 1
depicts all of these possible electrodes that can be combined to
form the three EGM sensing axes as described below.
[0067] The distal tip electrode 44 that is lodged into the right
ventricular apex is coupled through a conductor within lead 40 to a
ventricular event sense amplifier within the circuitry of the IMD
30. The ventricular sense electrode can also be connected to the
electrode 42 to provide near field, bipolar sensing. The sense
amplifier can be a conventional R-wave sense amplifier for
detecting the R-wave in the PQRST complex and declaring a
ventricular sense (VS) event (from which a fiducial point is
located) as described further below.
[0068] Device details and general operation to implement a process
for finding ischemia
[0069] Optionally, the IMD 30 can also include a therapy delivery
system for providing pacing, and/or cardioversion and
defibrillation therapies and/or vagal or carotid nerve stimulation
therapies as described in the above-incorporated '563, '428 and
'507 patents. The ischemia detection algorithm of the present
invention can be used to trigger or to modify a delivered therapy
to alleviate or avoid exacerbating the ischemic condition or to
avoid mistaken detection of a cardiac tachyarrhythmia due to
distortion of the EGM being monitored and processed for
tachyarrhythmia detection. For example, in a DDD or DDDR pacemaker,
the upper rate limit for tracking atrial depolarizations or P-waves
and providing ventricular pacing is normally programmed by the
physician to a fixed upper rate, e.g., 120 bpm. If the patient
suffers an ischemic episode, it would be desirable to lower that
upper rate to avoid pacing the ventricles at such a rate and
exacerbating the symptoms. In a tachyarrhythmia control device,
anti-tachycardia pacing therapies and, optionally, cardioversion
shock therapies are provided on detection of an appropriate
triggering tachycardia or life threatening flutter or
fibrillation.
[0070] In any of these contexts, data related to detection of
ischemia is stored in memory for later uplink telemetry
transmission and analysis by the physician. The IMD 30 may also
include an audible alarm or a stimulation of the patient's skin to
alert the patient to the detection of ischemia and/or a patient
activation mechanism by which the patient can trigger storage of
data into a memory circuit in the IMD, or even trigger therapy to
be administered by the IMD, upon feeling angina symptoms. A real
time clock can also be included in the IMD system for storage of
the time and date of each stored ischemic episode, and therapy
delivery data can be stored in the therapy delivery IMD
context.
[0071] Turning now to FIG. 2, the circuitry 100 of the monitor or
therapy delivery IMD 30 for detecting conditions of ischemia and
storing ischemic episode data in a monitoring or therapy delivery
context are depicted in a simplified exemplary form. Clearly one of
ordinary skill would recognize that the thicket of signal lines one
would ordinarily use to communicate timing and control signals and
the like among the circuit blocks shown are irrelevant to the
performance of the inventive functions herein described. Likewise
the use of a bus, 301 to simplify communications pathways as shown
may be preferred in some device builds, however they would also
recognize that the memory may serve to house the buffer circuits
described with reference to FIG. 3 as well as serve the
microprocessor, or that it may be more efficient to build them
separately. Further the system of FIG. 2 could be preferably
implemented employing custom integrated circuit technology
including a microprocessor 110 and associated RAM/ROM chip 140 and
related circuits and data buses. Because FIG. 2 is intended to
depict circuitry for a device which can provide both monitoring and
therapy delivery functions through devices like those IMDs of FIGS.
1A and B, it depicts the optional therapy delivery system 170
selectively employed in the therapy delivery IMD embodiments within
broken lines. An external device such as is illustrated in FIG. 1C
(or an implantable device used only for monitoring) could exclude
boxes 170A, 170B and possibly the patient activation box 160, if
desired. A patient activation mechanism 160, which may be a switch
closed by a magnetic field that the patient brings over the skin
with a magnet brought to overlying the IMD 30 when the patient
feels ischemia symptoms, can also be provided for initiating
storage of EGM data or delivery of limited therapies. Likewise, an
external device or programmer like device 13 of FIG. 1A could be
used to activate storage, transmit old stored records, cause
delivery of real time multi-channel telemetry and so forth, if the
telemetry circuit 120 is used to initiate such functions. The
battery and power supply circuitry to all of the functional blocks,
the crystal oscillator and clock circuits for timing circuit
operations, and certain other functional blocks associated
typically with a digital controller/timer (DCT) circuit or the
microprocessor 110, as well as other features common to pacemakers,
cardiodefibrillators, drug pumps and/or neural stimulators are
common and are therefore not shown to simplify the illustration and
focus this exposition on the invention. To illustrate here, there
needs to be a therapy delivery system such as a controlling circuit
170A and a delivery circuit 170B to deliver the therapy indicated
by the presence of ischemia conditions confirmed or found using
this invention.
[0072] Many of the operating parameters and modes and the
above-described sense electrode selections can be programmed from
outside the patient's body by a programmer of the type described in
commonly assigned U.S. Pat. No. 4,550,370, incorporated herein by
reference. The external programmer is operated in a downlink
telemetry mode wherein telemetry transmissions are effected through
a telemetry antenna 130 and an RF telemetry transceiver 120. Data
related to ischemia episodes that is generated in real time or is
stored in RAM/ROM chip 140 can also be transmitted to the external
programmer in an uplink telemetry mode using the RF telemetry
transceiver 120 and antenna 130 in a manner well known in the prior
art.
[0073] The basic operation of this circuitry 100 is as follows. The
electrodes selected by select line 111 under microprocessor control
determine the configuration of the switch assembly 180. This passes
the signals to the signal processing circuit 300, which can convert
them to digital values for storage in buffers, which may be in
memory circuit 140. Indications of R wave peak timing and the
presence of an R wave detection may be forwarded to the
microprocessor circuit directly on lines 342 or 344, or be
retrieved from locations in memory depending on how the system is
configured. The microprocessor circuit under program control will
follow the procedures for manipulating the data values stored in
the buffers as described in detail starting with FIG. 6.
[0074] Likewise under program control, the microprocessor 110 will
direct signals to the therapy delivery control circuit(s) 170A as
indications of ischemia are required by the programs for the
particular therapy control circuit 170A it is addressing.
[0075] Further, patient activation may cause the storage of
buffered data or portions thereof under program control executed by
the microprocessor. Either patient activation or an external
programming device such as device 13 of FIG. 1A can send signals
through telemetry antenna 130 and circuitry 120, to accomplish
these patient activation functions and other functions alluded to
earlier in this discussion. If desired the microprocessor will
activate the direct telemetry of a representation of the analog EGM
signals across lines 113, which in the preferred embodiment will be
three EGM signal lines for three channels, as the signal
transpires.
[0076] The ST segment signal processor 300 is depicted in greater
detail in FIG. 3, selectively coupled at its input terminals to
electrodes which may be selected by the microprocessor, here
connecting electrodes "A", -"E" to three differential amplifiers
103, 105, and 107 so as to produce the vector signals A-B, B-C, and
C-E at the output of amplifier stages 109, 111, and 113. The
electrode D is operating as a body ground to let the variation in
background signal in the body be somewhat washed out, by connecting
it to the ground input of the three differential amplifiers 103,
105, and 107 Another way to describe the value of Electrode D in
this context as a body ground is for rejection of common mode
signals by the three differential amplifiers. Thus in the
orientation described from these electrodes in FIG. 1B, amplifier
113 produces an electrocardiogram vector between the connector
block electrode A and the one potentially mounted into the back of
the body E, or in the A-P plane. Electrodes B-C and A-B are in the
coronal plane providing rough correspondences with the plane formed
by the axes SI and LM. As stated before other configurations are
allowed.
[0077] The microprocessor can allow these analog electrocardiogram
waveform signals to be sent directly to telemetry through the
SWITCH circuit, controlled by the microprocessor, preferably or
directly by an outside signal from the patient activation circuit,
so that analog tracings can be viewed instantaneously outside the
patient's body. The output of these amplifiers 81, 83, and 85 would
thus be sent to the telemetry circuit 120 of FIG. 2.
[0078] The signals are also, of course, sent to the Analog to
Digital Circuit ADC 95 so they can be converted to digital values
and fill the two triple buffers (one for each vector) 71. With a
shift buffer 72 included, the output of the 160 millisecond buffers
71 and the 320 millisecond (after the R-wave) buffers 73 can be
output onto the data bus together, but the hardware designer of
ordinary skill in this area may provide for alternative
arrangements to output the sampled and digitized output signal
values than is shown here. Also shown is the means by which the
output of the ADC can be diverted between the buffers 71 and 73,
here the R-Wave peak detector.
[0079] It must be recognized that these could be electrodes A-E
from FIG. 1B, or any other set of input electrodes for the purposes
of this invention. The important thing is that a set of vectors,
that is more than one, are available, each of which corresponds to
some orthogonal vector in the anatomical structure of the patient
being looked after. In this illustrative example we use 3
electrodes and 3 pairs for inputs to the input amplifiers, but one
could adopt 3 electrodes to two input amps or 5 to 4 amps, and so
forth if desired, with a corresponding decrease or increase in the
number of available vectors for processing. Also the selective
combinations can be made through programming the programmable
switch assembly 180 or can be permanently made at the time of
manufacture of the IMD 30.
[0080] However they are selected, the ST signal processor 300
provides the orthogonal EGM signals or lead vectors labeled A-B,
B-C, A-E, to indicate they represent the signal across these inputs
from corresponding electrodes in the patient's body, be they SEA or
lead tip (or ring-type or defibrillator type) electrodes. They can
be sent out for real time reading to an external device by sending
them to the telemetry transceiver 120 for uplink transmission in
real time in response to a command received via a downlink
telemetered interrogation command if desired. Or they can simply be
used by the IMD itself.
[0081] The ST signal processor 300 samples and digitizes the
orthogonal EGM signals S-I, L-M, and A-P at a certain sample rate
(example rates include 60 to 256 Hz, and should be selected mainly
based on the resolution desired and the available processing power;
in the preferred examples we use 120 Hz). The processor 300
temporarily stores the sample values. The ST signal processor also
processes the sensed R-wave derived by the ventricular sense
amplifier coupled to a selected sense electrode pair 44 and 42 or
58, for examples, and derives an R-R interval that is provided to
the microprocessor on line 342. The sensed R-wave is also used to
trigger storage and transfer of a number of sample values of the
orthogonal S-I, L-M, and A-P lead vectors preceding and following
the sensed R-wave to the microprocessor 110 via data bus 340. The
microprocessor 110 processes the plurality of EGM signals pursuant
to the algorithm described below to derive an ST parameter signal
that is compared to a programmable ST segment threshold to declare
the existence of ischemia if it exceeds the ST segment threshold
and deliver a therapy and/or store data related to the ischemia
episode. It will be understood that there may be one to three ST
parameter signals derived from the three EGM signal vectors that
are compared to a single ST segment or ischemia parameter
thresholds stored in memory or to three such dedicated ischemia
parameter thresholds. The ST segment signal processor 300 preferred
process for deriving the ST parameter signals is set forth in the
flow charts commencing with FIG. 6.
[0082] It should be noted that the R-wave peak detector can be as
described in detail herein or one could use other reliable methods
for determining the R-R interval or the start of an R-wave. It is
important that some determination be made so that processing can
begin on the buffered data, thus the appearance of an R-wave is
linked to a particular data sample as will be described in detail
below.
[0083] The measurement of the ST segment deviation along each
sensing axis involves defining a set of sampled time points in a
measurement window timed from the detection of the R-wave or the
R-wave peak. FIGS. 4 and 5 are EGM waveforms of exemplary PQRST
complexes during cardiac cycles illustrating non-ischemic and
ischemic ST segment deviation, respectively. Sample points 1, 2, 3
and 4 are employed in the ST segment processing algorithm of a
preferred embodiment of the invention. Myocardial ischemia results
in multiple changes in the EGM waveform data sets designated for
each vector. We prefer to have orthogonal vectors and may designate
them as S-I, L-M and A-P vectors assumed to be derived from between
three different selected electrode pairs. These changes in the EGM
signals caused by myocardial ischemia may include ST segment
elevation or depression, changes in R-wave amplitude, T-wave
inversion, increase in Q-T dispersion, and alternans, which is
characterized by different PQRST morphology of alternate PQRST
complexes. The changes in the ST segment deviation and polarity are
the easiest to detect, are the most recognized and accepted signs
of ischemia by physicians, and are likely to be the most sensitive
and specific signs of ischemia that can be derived automatically
from the EGM using an algorithm.
[0084] In the non-ischemic EGM waveform of FIG. 4, the disparity
between the isoelectric or baseline level as sampled at point 1
preceding the VS event and any of the sample points 2, 3 and 4
during the ST segment between the fall of the R-wave and the
termination of the T-wave is slight. By contrast, the disparity
between the isoelectric or baseline level sampled at point 1 and
any of the sample points 2, 3 and 4 during the ST segment
illustrated in FIG. 5 is great and can be readily detected by
thresholding techniques.
[0085] However, it is necessary to consistently locate the
isoelectric periods and the ST segment with confidence despite
variation in the heart rate that shortens and lengthens the ST
segment and other conditions that distort the ST segment amplitude,
shape and length including electrical noise signals that are
superimposed on the EGM waveform and vary the instantaneous ST
segment amplitude and axis shifts, cardiac pacing, etc. For
example, low amplitude 50 Hz or 60 Hz electrical noise is shown
superimposed on the EGM waveforms of FIGS. 4 and 5. This noise can
be filtered out during the sample point value measurement in a
manner described further below, or as desired. It is certainly
preferable to remove the cyclic noise.
[0086] The detection of the R-wave starts the process of
determining the fiducial point in the cardiac cycle from which the
sample points for sampling the signal amplitude in the isoelectric
region and during the ST segment are accurately timed. The most
readily recognizable and detected fiducial point of each cardiac
cycle is the positive or negative R-wave peak or R-peak which
exceeds the preceding P-wave by a substantial margin when the
R-wave sense electrodes are located in or on the ventricles. (One
could use the timing from the kind of R-wave detectors used in
pacemakers more typically, but we prefer what appears to be a more
certain point in the R-wave cycle so we adopt this method of
finding and using the R-peak point). The R-wave can be detected
between any two electrodes, for example, lead tip electrode 44 and
lead electrode 42 or one or the unused SEA electrodes 50-60 using a
simple bandpass/derivative filter followed by a slew rate threshold
detector that operates similar to a conventional R-wave sense
amplifier that is also blanked for a time period after detection.
Such an R-wave sense amplifier 302 that generates a VS event signal
and is then blanked in this manner is included in the ST signal
processor 300 depicted in FIG. 3. In accordance with one aspect of
the preferred ST segment processing algorithm of the present
invention, sampled data points of the sensed EGM signals S-I, L-M,
and A-P (or A-B, B-C, and C-E) which have been collected into the
buffers are used for processing when the VS event is detected,
preferably by the sense amplifier 99. The data points closest to
the actual R-peak of each of the sensed EGM signal sets are
determined, and the sample points 1, 2, 3, and 4 (from FIGS. 4
and/or 5) are captured relying on the fiducial point; the peak of
the R-wave; in our preferred embodiment.
[0087] The amplitudes of the orthogonal EGM signals or lead vectors
S-I (A-B), L-M (B-C) and A-P (C-E) may be sampled at an 8 ms sample
rate (120 Hz sampling frequency) and digitized in parallel in the
ADC block 95 to continuously generate data points that are entered
into three parallel 160 ms buffers in block 71 on a FIFO basis. The
digitized sample points of each of the orthogonal EGM signals may
also be applied directly to RF telemetry transceiver 120 for real
time uplink telemetry transmission when that operation is enabled
as described above.
[0088] The VS event signal is generated on line 344 when the R-wave
sense amplifier 302 detects an R-wave, and the R-wave sense
amplifier 302 is then blanked for a set blanking period to avoid
double sensing of the same R-wave. The current R-R interval (i.e.,
the heart rate) may be determined from the previous VS event by an
R-R interval calculator in R-wave peak detector 97 or which
operation could be performed by microprocessor 110 in response to
the successive VS event interrupts. In a pacemaker or
cardiodefibrillator other circuits may provide R-wave or VS
detection signals as well. The VS event signal is applied to
disable inputs of each of the three 160 ms buffers in block 71 to
disable them from receiving further data points on bus 340 from the
ADC. The buffer contents, comprising all the digitized sample
points of each signal S-I, L-M and A-P prior to the VS event, are
passed through parallel transfer logic block 72 to the
microprocessor 110 via data bus 340. At the same time, three
parallel 320 ms buffers in block 73 are enabled to receive the next
40 data points ( when sampled at 120 Hz, about 80 if at 256 Hz)
sampled from the three EGM signals until they are filled. When they
are filled, the contents of the three parallel 320 ms buffers in
block 73 are transferred on data bus 340 to microprocessor 110.
[0089] It should of course be recognized that the vectors for
sampling the electrocardiogram signals may be determined by a
physician, or set up in accord with a testing program or simply be
set as a default.
[0090] The microprocessor 110 temporarily stores the transferred
data points in RAM in RAM/ROM chip or memory 140 for determination
of the sample point closest to the R-peak, the isoelectric data
point 1 and the three ST segment points 2, 3 and 4 of FIGS. 4 and 5
in relation to the R-peak sample point and for further processing.
The 60 data points that are transferred on data bus 340
representing each EGM signal or lead vector S-I, L-M, and A-P are
preferably processed in parallel.
[0091] The general algorithm
[0092] FIG. 6 sets forth a high level block diagram of the main
steps or stages of performing the ischemia detection method of the
present invention that is preferably implemented by a program in
memory, used by the microprocessor 110. In step 1, or Step S100
simply the standby function is performed between VS events that
involves the continuous sampling of the signal levels of each
selected input electrode pair, and temporary storage in the
buffers. As described above, when the VS event is recognized, a
group of samples are stored from before the event, and a larger
group of serially obtained samples are stored after that.
Preferably, at least 16 samples (128 ms) are taken before the VS
event (the suprathreshold sample) and 40 samples (320 ms) after the
VS event of the PQRST complex of that cardiac cycle; and these
samples are stored in the three parallel buffers (one for each
vector or lead), to be subsequently passed via data bus 340 to the
microprocessor 110. Thus we can mark the sample coincident in time
with the VS event and have collected another 30-50 samples at the
preferable rate of 120 Hz, after the VS event.
[0093] The second stage, step 2, of FIG. 6 comprises steps
S110-S139, shown in FIG. 7, wherein data values for each of the
R-peak, the isoelectric point 1, and the ST segment points 2, 3 and
4 are identified, thus locating the features of primary importance
to us in the waveforms such as those illustrated in FIGS. 4 and 5.
This can be done under program control by the microprocessor using
memory in the buffers themselves or in a separate memory as
desirable.
[0094] In step 3, the data is "parameterized." That is, the
features of the segment of ECG waveform are characterized. The R-R
interval is taken, the R-wave slope figured, a value determined for
the noise in the isoelectric segment, the slope of the ST segment
found, a parameter called ST Change is found and the R-wave peak
amplitude is found, all in steps S140 to S159, described in more
detail below with reference to FIGS. 9-11.
[0095] In step 4, a determination must be made as to whether there
has been an axis shift in the vectorized ECG waveforms. This
process is described with reference to FIG. 12, steps 160-179.
[0096] In step 5, steps S180-S199 of FIG. 13 are used to describe
how the parameters are compared to their expected ranges and how
the ranges are maintained.
[0097] Following step 5, in step 6, the ST Change signal values are
filtered in a complex process in order to evaluate the ischemic
condition of these vectorized ECG inputs. This takes numerous
inputs from the already performed functions in the preceding steps
and processes them in steps S200 to S240, explained with reference
to FIGS. 14-16.
[0098] With the now evaluated ischemia value, the system can
perform additional monitoring, therapy and alarm functions in step
S251, or simply continue collecting samples as in step S100 and
following the steps already outlined.
[0099] It is noted that the steps 1-3 and 5 of FIG. 6, provide a
separately useful process for any physiologic signal to be
determined using an electrocardiogram, such as T wave variation,
ischemic condition or QT variation, which could be used to detect
actual or incipient arrhythmias for example.
[0100] Also, the axis shift determination by itself may be used to
avoid using bad data from determination of such physiologic
indicators in the electrogram signal.
[0101] Further, the determination of an ST change signal value for
each (good) cardiac cycle and filtering it to determine an ischemia
parameter value can be done on unfiltered cardiac signals, cardiac
electrogram signals filtered in a different manner or taken without
axis shift determination, and accordingly it is believed to have
separate utility.
[0102] Finally, the closed loop functions have their own obvious
utility, treating ischemia, which can much more reliably be
determined by resort to the other independent features of this
invention.
[0103] The details of the algorithmic processing
[0104] In the steps illustrated in FIG. 7 and in other steps of the
algorithm, data point values are preferably averaged over at least
two samples (taken 8 ms apart) in order to obtain an average value
over a complete cycle of 60 or 50 Hz noise. The average value would
then be used for the data point. If a complete set of data points
is operated upon, this averaging can be done at any stage in the
process as should be recognized by anyone of ordinary skill in the
data manipulation arts. FIGS. 8A-8C illustrate this noise filtering
technique in three cases where the successive sample points fall in
different phases of a 60 Hz noise signal cycle. The algorithm is
made indifferent to 60 Hz AC noise through the use of this
technique.
[0105] Referring now to FIG. 7, steps S110-S114 illustrate the
process of locating the data point values closest to the actual
R-peak within the buffered samples that were preferably taken
substantially as described with reference to FIGS. 2 and 3. The
R-peak value may be either a positive or a negative value,
depending upon the orientations at which the vectors were collected
and sampled, relative to the depolarization wave originating from
the heart. In step S110, a preliminary isoelectric point is
selected as the average values of the 8.sup.th and 9.sup.th sampled
data point values that were stored in the buffers prior to the VS
event interrupt. (Recall that the VS event interrupt may be based
on a determination of a ventricular depolarization wave occurring
though any method/apparatus for determining a VS event known in the
art and using it to generate a signal. The samples 8 and 9 are
prior to the VS event in the buffer).
[0106] Then, in step S112, the minimum and maximum data point
values are found in the samples taken about the time of the R-wave
indicator signal, the VS event interrupt. They will be the largest
and smallest (or greatest positive and greatest negative) sample
values in the portion of the electrocardiogram collected in the
case of a relatively normal cardiac cycle. In the preferred
embodiment these are the sampled signal values taken within the 5
samples (40 ms) before the VS event and 7 samples (56 ms) after the
VS event. In Step S114, the program compares the differences
between the minimum value in these sampled values and the
preliminary isoelectric point data value and the maximum value in
these sampled values and the preliminary isoelectric point data
value. The difference that is larger indicates the orientation of
the vector from which it is taken and the value of that difference
which is larger is the assumed height of the R-wave for that
vector. That highest point (in absolute value) also then gives us
the important fiducial point for the peak of the R-wave within the
collected portion of the electrocardiogram. With the R-peak data
point determined for each vector of buffered data points, it is
used to determine the data points 1, 2, 3 and 4 indicated on the
ECG wave forms, examples of which are illustrated in FIGS. 4 and 5.
(This is done independently for each vector). Beginning at 5
samples (40 ms) before the R-peak sample, the algorithm marches
backwards in steps of to samples, searching for a local minimum in
the absolute slope between successive samples as illustrated in
steps S116-S124. (It will be understood by a programmer of ordinary
skill how to make a program sort through samples to produce this
algorithm. Detailing the setting up of a sort routine, comparisons
et cetera is considered well outside the range of needed disclosure
since these processes are translatable into software which can
operate the microprocessor to accomplish these algorithmic steps,
and will be necessarily different for every processor). A slope is
measured as the absolute difference between two samples that are
spaced apart by two samples. The two sample spacing is to avoid
measuring the slopes introduced by 50 Hz or 60 Hz AC noise which
would otherwise corrupt this search with this common noise
frequency, but is unnecessary if the noise is controlled for
otherwise. The search concludes when a local minimum of slope is
found, or when the search reaches the beginning of the stored data
points of the PQRST complex. The isoelectric point 1 value is then
averaged over 2 samples (16 ms). In FIG. 7, this procedure is
described with reference to steps S116-S124, as an algorithmic do
loop.
[0107] In Steps S126-S139, the ST segment measurements are
conducted at three locations in the collected and buffered
electrogram portion indicated by delays D1, D2 and D3 timed from
and following the R-peak. The delays D1, D2 and D3 for ST segment
data point value measurements are normally set at about 90 ms (or
about 11 sampled data points), 135 ms (or about 17 sampled data
points), and 180 ms (or about 22 sampled data points). In step
S139, the three ST segment data point values are therefore normally
selected at R-peak+90 ms, R-peak+135 ms, and R-peak+180 ms. Delays
D1, D2 and D3 are converted into data point buffer locations for
the full 480 ms buffer contents in step S139. The two successive
data points in the buffers that are closest in time to each such
adaptive delay are averaged in step S139 to derive the actual
sampled ST segment value.
[0108] However, the three delays D1, D2 and D3 depend on the
current R-R interval and are therefore adjusted in steps S126 and
S128 to be proportional or adaptive to the current heart rate. For
example, at faster heart rates, the ST segment is closer to the
R-peak; therefore, the three delays D1, D2 and D3 are shortened
proportionally (in an inverse manner) with the change in rate. In
step S126, we use a preferred delay factor calculated as equal to 4
times (1 second minus the current R-R interval). If however the
heart rate is less than 60 bpm, thus making the R-R interval larger
than 1000 ms, the delay calculation step will still report zero as
output. For example, the delay factor is 2.0 when the R-R interval
is 500 msec and the heart rate is 120 bpm. In step S128, the delay
factor is used in the depicted equations to adjust the delays D1,
D2 and D3. For example, if the heart rate is 80 bpm, the R-R
interval is 750 ms, and the delay factor is 1 calculated in step
S128. The delays D1, D2 and D3 are expressed in numbers of 8 ms
sample points. Therefore the rate adjusted sampling points are
subtracted from the numbers 8, 15 and 22 in step S128, yielding
sample points of 7, 13 and 19 (times 8 ms, the sampling period)
from the peak of the R-wave, corresponding to 56 ms, 104 ms, and
152 ms, respectively, from the R-wave peak, to the right if you are
reviewing FIGS. 4 and 5. These delays will then provide pointers to
the sample values at the preferred locations for points 2, 3, and
4.
[0109] Before referring to FIG. 9, please consider where we are in
relation to FIG. 6. In the third stage (steps S140-S159) of FIG. 6,
seven different waveform parameters are derived as shown in FIGS.
9-11 to characterize the PQRST waveforms. Some of them may be
derived from each of the vectors and some are derived from a
combination of vectors, represented by the sampled data point sets
for each of the three electrode pair vectors. The programmer of
ordinary skill can easily build an algorithm to process the
buffered data representing the sampled signal values to produce the
parameterization described in the following description. The seven
waveform parameters which are made from the buffered data are as
follows.
[0110] 1. The R-R interval parameter (step S140), which can be kept
for each vector or the same one used for all further calculations
as desired.
[0111] 2. The R-peak jitter parameter, i.e., the variation in
relative timing of the R-peak data points in the three lead vectors
(step S141). If there are 3 vectors, three values are determined,
if 2 only one, if 4, 6 values are preferably determined and
stored.
[0112] 3. The R-wave slope parameter of the three R-waves of the
three lead vector PQRST complexes (steps S142-S144) is taken for
each vector.
[0113] 4. The combined NOISE parameter representing noise in the
isoelectric segment (steps S146-S148). This can be done for each
vector or averaged and only one value used. We prefer using only
one value.
[0114] 5. The ST segment slope parameter of the three ST segment
measurements (2, 3, and 4) of the three lead vector PQRST complexes
(step S150). There preferably should be a value found for each of
the vectors for this parameter.
[0115] 6. The ST segment change parameter (step S152). There should
be one for each vector.
[0116] 7. The R-peak amplitude parameter of the three R-waves of
the three lead vector PQRST complexes (step S159). There should be
one of these for each vector.
[0117] These parameter values are then used in the axis shift
determining stage (steps S160-S179) and the parameter checking
stage (steps S180-S199). If no axis shift is detected and if the
current parameters satisfy the parameter checks, then the ischemia
parameters are determined and compared to the programmed ST
parameter thresholds in the final stage (steps S200-S240) before
being recorded in memory for later use, used for altering therapy,
and so forth.
[0118] In step S140 (FIG. 9), the R-R interval data may be
retrieved from an R-R interval calculator specifically subtracting
time elapsed values from R peak to R-peak, or keeping a log and
reporting out the value of elapsed times. Or, the value of the R-R
interval may be derived from another process in the implantable
device, borrowing the data from interval timers that already exist
in pacemakers, cardiodefibrillators and the like. This value (from
whichever source is preferred) is stored for the R-R interval
parameter for this R-wave's set of buffered data.
[0119] Recall that in step S114 of FIG. 7, the three R-peak values
were calculated for the data points for the three lead vectors. The
relative timing of the R-peak data points in the three lead vectors
is determined in step S141 of FIG. 9 to determine an R-peak jitter
parameter. High amplitude noise will likely cause disparities in
R-peak detection timing in the three lead vectors. (The timing of
the R-peaks in our preferred embodiment must be within the expected
range(discussed below with respect to FIG. 13) to be accepted.)
[0120] Then in step S142-S144 shown in detail in FIG. 10, the
R-wave slope parameters of the three R-waves of the three lead
vector PQRST complexes are calculated. In each case, the first and
second sampled data point levels prior to the R-peak data point
value are located in steps S142 and S143. In each case, the
absolute value of the difference between the first and second
sampled data point levels prior to the R-peak data point value is
determined in step S144. The actual R-peak data point value is not
used because it is not known if this data point value is on the
rising or falling edge of the R-wave. Thus, the slope figured for R
is the absolute value of the first point minus the second
point.
[0121] The noise in the isoelectric segment is calculated in steps
S146-S148 as the sum of the absolute differences between the
isoelectric data point value (which, preferably, is an average of 2
samples, itself) and preferably three sample data point values
including the two points used to find the isoelectric data point
value. The three data point values are located in step S146.
[0122] In step S147, the absolute differences from the three data
points and the ISO1 point value found in step S146 for each lead
vector are summed together. In step S148, the sums arrived at in
step S147 are summed together to derive a combined NOISE parameter
value for the current PQRST complex. (One could easily average them
too, but as long as the processing is consistent from each cardiac
cycle's portion of data, there is no need for the extra processing
step averaging the vector's noise values would entail). This value
NOISE can then be used to determine if the samples collected for
this cardiac cycle are acceptable from a noise standpoint or should
be discarded. This noisy signal rejection could be done here or the
noise value stored for later processing.
[0123] Three ST segment slope parameters are calculated in step
S150 as the absolute value difference between the first and second
ST segment data point values taken for each lead vector. The ST
segment change parameter for each lead vector is calculated in step
S152 as the difference between the mean of the three ST data point
values and the isoelectric data point value. The R-peak amplitude
parameters are calculated as the difference between the value taken
at the R-wave peak data point and the isoelectric data point of
each of the three lead vectors in step S159.
[0124] The combined single parameter values derived in steps S140,
S141 and S146-148 and the individual parameter values for each lead
vector derived in steps S142-S144, S150, S152, and S159 are
preferably retained in registers for use in the following steps of
the algorithm until they are replaced when the next PQRST complex
is processed in the steps S100-S139 described above.
[0125] Dealing with Axis shifts
[0126] Rapid changes in the electrical axis of the heart can cause
rapid changes in the ST segment which are not associated with
ischemia (see Adams et al., J. Electrocard. 1997: 30:285, and Drew
et al., J. Electrocard. 1997; 30(suppl): 157). Such axis shifts are
most often caused by a change in posture. For example, an axis
shift can cause an immediate deviation of the ST segment that can
mistakenly be classified as representing onset of ischemia if the
sampled ST segment value is compared to and exceeds an ST segment
threshold.
[0127] In the present invention, as described in detail with
reference to FIG. 12, axis shifts are tracked and compensated for
automatically. The seven parameters derived in steps S140-S159 and
processed in steps S180-S199 will be used to determine if a
satisfactory number are within defined narrow "expected" range and
all are within an expanded range. In steps S160-S179, if an axis
shift is detected, its detection causes a type of "reset" of the
algorithm. In this reset process, expected ranges of all of the ST
segment parameters determined in steps S140-S159, except the R-R
interval parameter, are instantly broadened. This allows the
expected ranges to adapt to the new steady-state parameter values
that occur in an axis shift, thus allowing for the retention and
use of valuable data samples in the presence of axis shifts while
avoiding false positive ischemia detection.
[0128] FIG. 12 shows the preferred implementation of the axis shift
handling steps. The R-wave amplitudes are first compared to their
expected ranges in step S160. If the R-waves are within the
expected range, the count of an Axis Shift counter is decremented,
as long as it is greater than zero, in step S162, and the count of
the Axis Shift Flag counter is also decremented, and then the
R-wave axis shift procedure waits for the next set of data from the
next cardiac cycle. If the R-wave amplitude is out of range, the
Axis Shift counter is incremented in step S166. The count of the
Axis Shift counter is compared to 18 and the count of the Axis
Shift Flag counter is compared to 50 in step S168, keeping the
relevant number in an appropriate range. If these conditions are
not met, then the count of the Axis Shift Flag counter is
decremented in step S164 and the procedure is again finished for
this round.
[0129] If an axis shift is declared in step S168, and the allowed
ranges of the seven waveform parameters are broadened by a factor
of three in step S179 when the count of the axis shift counter
exceeds 18 and the count of the Axis Shift Flag counter is less
than 50. In addition, the count of the Axis Shift Flag counter is
set to 100 in step S170 in order to limit multiple axis shift
detections from a single axis shift event. The count of the Axis
Shift Flag counter is subsequently decremented by 1 each cardiac
cycle in step S164.
[0130] Thus a kind of filter is established which generates an axis
shift response signal (broadening the ranges) if there is a jump
out of range for long enough to cancel the occasional short term
indicator of a shift that is noise, but not allowing for a rapid
series of axis shifts to make the expanded range meaninglessly
broad.
[0131] The steps in FIG. 13 determine if we will use the data from
a given cardiac cycle for determining ischemia. They also permit
the acceptable ranges for the parameters to be adjusted. In FIG.
13, the seven waveform parameters for noise detection (defined in
the steps S140-S159) are compared to adaptive "expected" expected
ranges at two different levels ("near" and "far"). The system
preferably maintains values for a mean and mean absolute difference
(MAD, like a standard deviation but easier to calculate) of the
paremeters in a memory location or register set, and determines if
the current parameter lies within the MAD of the mean to the
positive and negative side of the mean, that is, within an expected
range. Clearly other ways could be used to set the expected range
for the parameter, but this seems preferred for implantable
devices. In one preferred form, to find the expected range, the MAD
is multiplied by a constant, thus the expected range is the mean
+/- range*MAD. In the block diagram of FIG. 13, the "far" expected
range is exactly twice as large as the "near" expected range. The
extent that the waveform parameters are out of range affects how
the current cardiac cycle is used to update the expected ranges. If
more than 2 of the 7 parameters are out of the "near" expected
range, the current cardiac cycle is not used to update any of the
expected ranges or to detect ischemia. Additionally, any individual
parameter that is outside the "far" expected range is not updated
by the current cardiac cycle. For example, if the ST Change
parameter is within the "near" expected range of the running mean
+/-2.times.(running mean absolute difference [MAD]), the ST Change
parameter is not considered "noisy". If the ST Change parameter is
between the running mean +.-2.times.MAD and the running mean
+/-4.times.MAD, then the STchange parameter is "noisy" but the
current value is still used to update the mean and the MAD. If the
ST Change parameter is outside of the running mean +/-4.times.MAD,
then the ST Change parameter and all of the filters that are used
to estimate the ischemia parameter are not updated by the current
cardiac cycle.
[0132] If individual parameters consistently fall outside of the
"far" expected range, e.g., for 12/12, 13/14, 14/16, etc. beats,
then the algorithm considers the parameter to have made a step
transition to a new state (i.e., a sudden change in rhythm). In
this case, the allowed range is forced to expand exponentially (by
multiplying the value of the current MAD by 1.06 every beat) until
the parameter is back into the "far" expected range. After
re-establishing the parameter, the allowed range will slowly shrink
to fit the current rhythm. In this way, the algorithm adapts to
accept any rhythm from any patient, but is able to reject transient
episodes of arrhythmia or noise corruption.
[0133] A block diagram of the parameter comparison and expected
range updating process of steps S180-S199 is presented in FIG. 13.
Beginning at step S180, the expected ranges for each parameter
within each vector, if relevant for that parameter, is calculated
based on the last MAD and the new parameter value from the current
sampled waveform. Then the process in step S182 determines if each
current parameter value is within two times the value of the
expected range, if they are, S186 a PARAMERR counter is decremented
for that parameter down to zero where it would stay if it gets that
low. If however the parameter being checked is not within 2.times.
its expected range, the PARAMERR counter for that parameter will be
incremented in S184. If the result of incrementing this PARAMERR
counter is that this has been incremented often enough that there
is a clear change, manifest as an abrupt change in value for that
parameter (here we use a counter value of 12 as the preferred
level). Then step S188 will start the process of modifying the MAD
to let the range for this parameter to expand toward the change in
step S189. In all events (captured by using three counters in the
preferred embodiment, a decremented, an incremented but not up to
12, and an incremented over 12 PARAMERR counter for this parameter)
the process is repeated for each parameter, until all the
parameters are reviewed.
[0134] It should be clear that parameters from multiple vectors are
first combined to result in 7 parameters, total. That is, 3 R-Wave
slopes combine such that the R-wave slope is in the expected range
only if all 3 of the R-wave slopes are within their respective
expected ranges. Or, in some preferred embodiments, if the combined
vector parameter for the R-wave slope is within its expected
"space" then the R-wave slope parameter is within its expected
range (Refer to FIG. 20 for explanation of expected space).
[0135] At step S190, all the parameters are compared with their
expected ranges to determine whether we have a bad cardiac cycle of
information. At steps 192, if more than a sufficient number of
them, we prefer a majority of them (here>4/7 is preferred) are
within the expected ranges, we decrement a BADCYCLE counter (again
until it reaches zero). If the reverse is true, we increment the
BADCYCLE counter. When the BADCYCLE counter is incremented, the
current cardiac cycle is excluded from the process of updating
expected ranges and from the calculation of the ischemia parameter.
However, if the incrementing and decrementing leaves us with a
counter value greater than 12 (our preferred threshold value, but a
close number may be all right too), we suspect that an abrupt
change in cardiac rhythm has occurred, and the expected ranges must
be allowed to adapt to the new steady state. Therefore, these "bad"
cycles are included in the process of updating the expected ranges
and in the calculation of the ischemia parameter. Finally, an
additional criteria is imposed before the current value of a
parameter is allowed to be included in the process of updating its
expected range: The current value must be within twice the expected
range (step 197). This is a simple way to exclude outlier points
from the adaptive process, while including enough points outside
the expected range to keep the range from narrowing too much so as
to permanently exclude useful data outside the expected range. More
complex formulae ore even changing the valueof the 2.times. the
expected range could be used but this is the easiest one we found
to apply and one which worked well. All reasonable variations
within the skill of the ordinary practitioner would be considered
within this teaching, so long as they resulted in the points
allowed being within some range beyond the expected range. The
expected ranges are updated by combining a fraction of the current
value of the mean or MAD (given by the variable "A" in FIG. 13,
S198, which is preferably 90% or greater), with a small fraction of
a new estimate of the mean or MAD (the "(1-A)" term in the
equations in S198). This process is equivalent to filtering with a
first order infinite impulse response filter. It is similar to an
exponential moving average process and variations on it will be
apparent to those of ordinary skill.
[0136] After the expected ranges of qualified parameters are
updated (step S198) the algorithm can move on to the important step
of calculating the ischemia parameter. In Step S199 we place on
final constraint for candidate cardiac cycles before the data from
them can participate in the calculation of the ischemia parameter.
The ST change parameter must be within twice its expected
range.
[0137] To summarize, in order for the sampled data taken from a
particular cardiac cycle to be used in calculation of the ischemia
parameter, it must: (a) have>4 out of 7 of the parameters within
their expected ranges, or have 12 of 12, 13 of 14, 14 of 16 . . .
of the most recent cardiac cycles rejected by the 4 out of 7
criteria, and (b) the current cardiac cycle must have its ST change
parameter within twice the expected range for the ST change
parameter. If both these requirements are met, we go to step 200,
otherwise back to step S100.
[0138] FIGS. 14-16, combined together, are a block diagram of the
steps S200-S240 of the final stage of FIG. 6 wherein the ischemia
parameter is calculated and compared to the programmed ischemia
parameter threshold. The basis of the ischemia parameter is the ST
Change parameter (calculated in step S152). For each of the three
lead vectors, the ST Change parameter is passed consecutively
through a "Fast" lowpass filter in step S200 and the resulting
"FastST" signal is then passed through a "Slow" lowpass filter of
steps S202-230 (depicted in FIGS. 15 and 16)
[0139] The Fast lowpass filter of step S200 is preferably a
2.sup.nd order Chebychev Type II filter with a cutoff near pi/20
(radians per cardiac cycle) which excludes fluctuations of the ST
Change parameters that occur faster than physiologic ST deviation
changes. The filter characteristics are tuned from empirical data
of human ischemic ST deviation changes. Other filters may be used
including for example a Butterworth, or any other filter one of
ordinary skill in the digital signal processing art might employ.
The important feature is that the filter allow to pass primarily
that part of the ST change signal that changes no faster than
physiologic changes consistent with human cardiac ischemia.
[0140] The Slow lowpass filter is a complex nonlinear adaptive
filter set forth in steps S202-S230 which is designed to pass only
the baseline drift, i.e., the positive or negative deviations from
the baseline caused by drift, as an absolute "SlowST" absolute
signal, which we might call an `ST baseline signal.` The ischemia
parameter is then derived as the absolute difference between the
FastST and SlowST signals, normalized by a normalization factor
proportional to the R-wave amplitude or vector magnitude in step
S234. A bandpass filter is effectively created in steps S200,
S202-230 and S234 by subtracting the SlowST signal from the FastST
signal for each lead vector. This approach is followed in
recognition that physiologic ischemic changes in the ST segment
fall in a bandpass region, where elevation or depression changes
that occur too fast are due to noise or axis shifts and changes
that are too slow are caused by medication, electrolyte
disturbances, or other forms of baseline drift. The bandpass filter
approach is designed to pass only those ST changes that are due to
ischemia.
[0141] The normalization factor (NF) is obtained in step S232 as a
running mean of the sum of three R-wave amplitude parameters(one
for each lead vector). Alternatively, the normalization factor
could be obtained as a running mean of the vector magnitude of the
R-wave vector.
[0142] In step S232, the "new NF" is derived in one of two ways,
depending on the current count of the axis shift flag counter. As
shown in FIG. 12, the axis shift flag count was either set to 100
in step S170 in response to detection of an axis shift or was set
to a count less than 100 in step S164 because the axis shift
criteria were not met. The "old NF" is abruptly increased by a
large amount, we use a factor of three when the axis shift flag
count is set to 100, so that a sudden change in the ST change
parameter that can result from an axis shift is not misinterpreted
as ischemia. The factor of three change is selected because it
provides a good indicator of an axis shift but the artisan of
ordinary skill could chose to recognize the axis shift in another
way.
[0143] If the ischemia flag counter is less than 100, the new NF is
derived from the formula "new NF=0.98.times.old NF+0.02.times.(Sum
of all R-wave amplitude parameters). This equation's numbers and
form of this equation are chosen to change the factor slowly so
that rapid changes in the R-wave amplitude will not cause rapid
changes in the ischemia parameter. Similar programmable equations
could be used which accomplish the same result within the ordinary
skill of the programmer/engineer.
[0144] Returning to step S234, each of the three ischemia
parameters (IP) for each lead vector (or spatial vector)is
determined from the formula:
IP=.vertline.(FastST-SlowST)/new NF.vertline.
[0145] In step S236, each ischemia parameter is compared to an ST
ischemia parameter threshold previously programmed into a register
in step S235. In preferred embodiments, three ischemia parameters
are added and compared to a single threshold. Alternatively, if any
one ischemia parameter exceeds its ischemia parameter threshold,
ischemia is declared by setting an ischemia flag in step S238.
Ischemia is not declared and the ischemia flag is cleared in step
S240 if none of the ischemia parameters exceed the ischemia
parameter threshold. The setting of the ischemia flag is employed
to trigger delivery of a therapy and/or storage of EGM and any
sensor data, and the algorithm returns to the standby stage S100 of
FIG. 6.
[0146] FIGS. 15 and 16 describe in detail the operation of the
nonlinear, adaptive "SlowST" filter in steps S202-S230. The purpose
of this filter is to update the "SlowST" parameter, by slowly
tracking either the "FastST" parameter or an internal parameter
called "STBL", which is an estimate of the very slowly moving
baseline of the ST Change parameter. The method by which SlowST is
updated depends on the status of the ischemia flag, the axis shift
flag count, an initialization flag (which preferably is active for
the first 100 cardiac cycles of operation), and the current values
of SlowST, FastST, and STBL. To decrease the rate of change of the
SlowST parameter, it is typically updated only on every fifth
cardiac cycle (step S212), whereas the STBL parameter is only
updated every fortieth cardiac cycle (step S207). The SlowST
parameter is updated rapidly when the initialization flag is set
(step 203), less rapidly when there is an axis shift (step S221),
and very slowly otherwise (steps S216, S225, S228, and S230).
[0147] Thus, in FIG. 15, the status of the initialization flag is
first checked in step S202, and if it is set, the values of STBL
and SlowST are recalculated in step S203.
[0148] We would adapt this system for devices having any kind of
leads and providing any kind of therapy. For example, refer to FIG.
1 in which the heart 10 pumps oxygenated blood out through the
aortic arch 12, which leads to the right subclavian artery 14, the
right common carotid 16, the left common carotid 18, the left
subclavian artery 20, and the thoracic aorta 22. Stretch receptors
located in the arterial walls in the aortic arch 12 and at the
bifurcation of the carotid arteries in the carotid sinus portion of
the neck may be stimulated by electrical pulses, as may other
cardiac system affecting nerve sites, to reduce the effects of and
possibly eliminate the danger of an ischemic situation found by our
system.
[0149] For example, the rate of the heart 10 can be restrained by
the right and left vagus nerves, and cardiac depressor nerves. The
cardio-inhibitory center of the nervous system exerts a tonic
effect upon the heart, via the vagus nerves, acting through what is
called vagal tone. With vagal stimulation, it is possible to slow
the heart rate down and allow more complete cardiac relaxation,
which may lead to less of a deleterious effect upon the cardiac
tissue caused by an ischemic condition. Accordingly knowing
something about an ischemic condition allows one to provide
assistance to the heart through affecting vagal tone, or through
taking various other measures. It might use for example a device as
described in U.S. Pat. No. 5,752,976 to warn a health care provider
of the situation, while perhaps stimulating the nerves directly
using the system of U.S. Pat. No. 5,199,428 (both incorporated by
this reference in their respective entireties).
[0150] Also, introduction of various medicaments can have similar
effects on vagal tone, and other biologically active agents can be
used to directly treat the condition of ischemia. To do so the
teachings of for examples, U.S. Pat. Nos. 5,458,631, and 5,551,849
may be used. Further, communication from one device sensing an
ischemic condition can communicate with other devices for providing
therapy using the teachings of, for one example, U.S. Pat. No.
4,987,897, The Funke Body Bus. Accordingly, the teachings of this
disclosure make it possible to know that ischemia is present and
thus allow for the opportunity to treat it.
[0151] Use of multidimensional versus multiple single-dimensional
"expected ranges"
[0152] By comparing each parameter from each vector to its own
independent expected range, the inter-dependencies of parameters is
not taken into account and the form of the expected range is highly
constrained. For example, comparing the two R-wave slope parameters
obtained from two lead vectors to two separate one-dimensional
expected ranges produces two results: First R-wave slope inside or
outside of its expected range and second R-wave slope inside or
outside of its expected range. If the two R-wave slopes are plotted
on a two dimensional graph, with the first R-wave slope plotted on
the abscissa and the second R-wave slope plotted on the ordinate,
the two independent expected ranges form an "expected rectangle".
The advantage of this type of comparison is that one result is
obtained, whether or not the R-wave slopes are inside or outside of
the expected rectangle. By carrying this analogy one step further,
the expected range of 2 R-wave slopes (taken for two electrode
vectors for example) can be defined as a circle in two-dimensional
space. In this situation, rather than asking if each of the two
R-wave slopes lies within each of the two expected ranges (each
defined by two parameters, the mean and MAD), we are asking if a
mathematical combination of the two R-wave slopes falls within an
expected space that is defined by only 3 parameters: the center and
radius of the circle. Since a multidimensional expected range can
take on any shape, we can include inter-dependencies of parameters.
For example, we may find that it is acceptable for one parameter to
take on a small value only if a second parameter has a large value.
This sort of inter-dependency is easy to implement with a
multidimensional expected range. Accordingly we only require a few
additional computational steps to define the range space in
whatever shape is preferred, and the currently determined values
for the particular parameter are checked by the same computation to
see if they are within the range shape. This is preferably done for
each of the parameters, and changes to the expected ranges are only
made when parameters fall within twice the expected range.
[0153] Use during cardiac pacing
[0154] Finally, it should be noted that these processes can be
applied during cardiac pacing even though the waveform in the paced
electrogram is not typically useful for such systems as we have
invented due to the morphology of the waveform generally having a
rapid change in the ST segment as a normal part of the profile. We
simply either raise the pacing rate to a fixed level for a small
number of at least three beats per minute and use only the data
from that three beat set, thus assuring ourselves of near exact
localization of the sample data points relative to each other
across the three cycles. Alternatively we could lower the rate to
allow the intrinsic beat rate to appear and after a short run use
those beats' data. As a third alternative, the fiducial point
(which was previously defined as the peak of the R-wave) could be
defined as the precise time that the pacing stimulus is applied for
a paced beat. In other words, simply adopting a fixed point in the
pacing pulse can be used to replace the hunt algorithm and
mechanism for finding the R-wave peak as the fiducial point. The
timing of the ST measurements would then be fixed relative to the
pacing stimulus to ensure that the ST measurements are conducted
consistently in the complex morphology of a paced electrogram.
[0155] Other illustrations
[0156] In FIG. 17, the R-R interval (thick line) is followed and
compared to its expected range (mean+/-3*MAD) identified by the
thin lines on this graph of interval size in seconds vs. time. At
about 550 seconds, the R-R interval line 101 passes well outside
the upper line 102 of the expected range for an extended duration.
The expected range remains steady for 12 cardiac cycles, waiting of
the noise to end. However, the process described above determines
that a new normal has developed and adapts (at the point of the
upward arrowhead, towards 580 seconds), moving up both lines 102
and 103 to accept the new normal variation.
[0157] FIG. 18 illustrates a moving ST change parameter, showing
two situations which will be filtered out, the ST drift, and the
axis shift situations, and the one case in which the rate of change
of hte ST change parameter is consistent with human myocardial
ischemia, thus giving the device a trigger to report an ischemic
condition, commit to a therapy option or otherwise provide a useful
response or data record. Notice that drift can cause a substantial
change in the ST change parameter but because the rate of change is
slow, the drift is excluded from the ischemia parameter result.
Similarly, axis shifts can cause a significant change in the ST
change parameter, but because of the rapid rate of change, the axis
shift is excluded from the ischemia parameter result. Two axis
shifts are shown at 105 and 106.
[0158] In FIG. 19, the ischemia parameter that results from the ST
change parameter run thorough the processes described above is
shown. Note that only the physiologically identifiable change
registers as a high probability ischemic event at 107.
[0159] In FIG. 20 area 201 is that formed by the independent
expected ranges of two parameters, let us say, R-wave amplitude
parameters for two vectors, for example. Compare this to a 2-D
parameter value "allowed ellipse" 202, formed by a combination of
the parameter values by some preferred limit function. Thus,
comparing 2 separate parameters to 2 separate 1-D allowed ranges is
comparable to comparing a 2-D parameter value to an "allowed
rectangle" as opposed to the ellipse defined by the limiting
function and the ranges of the two parameters. This could expand
the allowed space to beyond the rectangle by, for one example,
drawing a circle around the outside of the rectangle, thus
providing some flexibility in using this concept. If a shape
surrounding the rectangle provides enough assurance that both
parameters are OK, one could use such a function, whereas if any
change in the parameter is considered risky, the function
inscribing a smaller shape within the rectangle would be
preferred.
[0160] It will be apparent to those skilled in the art that the
electronics of the system described above are easily attainable
using available technology. The electronics may be embodied in
custom integrated circuit and software based microprocessor
technology and certain of the steps of the algorithm could be
reduced to hardware.
[0161] It will thus be appreciated that the present invention as
described above defines a system having distinct advantages over
previously existing systems for detecting ischemia. This system
features a high degree of specificity to ischemic conditions and a
high degree of flexibility for recognizing and, in therapy delivery
configurations, treating ischemic conditions and/or arrhythmias of
the heart frequently associated with coronary artery disease and
myocardial insufficiency.
[0162] It should be noted that additional information regarding
ischemia can be had from different sensors. For example, using an
accelerometer implanted in the apex of the heart using a lead
mounted sensor similar to what is described in U.S. Pat. No.
5,480,412 issued to Mouchawar, et al. (incorporated by reference
herein in its entirety by this reference), L. Padeloetti, et al in
an abstractissued in the 20th Anniversary of Cardiostim (17-3) has
found that the peak endocardial acceleration signal changes
correlate well with episodes of coronary artery occlusion.
Similarly, pressure sensors as are known for example, from U.S.
Pat. No. 5,535,752 (also incorporated by reference in its entirety
by this reference) in the heart could sense the pressure variation
resulting from an ischemic condition. (See also U.S. Pat. No.
5,025,786 issued to Siegel, also incorporated by this reference,
for pressure sensing for ischemia). Thus, with a corresponding
signal from such a sensor (which could have an electrodes mounted
on it for sensing electrical activity also within the heart to
produce another set of electrocardiogram vectors as well), a
redundancy signal can be established based on the pressure or
acceleration signal that will confirm, in an additional step in the
algorithm, that following an axis shift, keeping data, excluding
data and so forth is or is not appropriate. If, for example, such
an accelerometer or pressure sensor reports decreases in the
accelerometer or pressure signal which is tending to indicate that
an ischemic condition might be occurring at the same time there is
an ST change parameter indication of the same condition, then there
is a mechanical verification (pressure, acceleration) of the
electrically detected (S-T change parameter) event, and the
specificity of the ischemia detection can be increased. Therefore,
the most aggressive device therapy, patient alert, or diagnostic
option may be initiated when both parameters concur. If on the
other hand, the new sensor signal (Acceleration/pressure) does not
show signals that correspond well to ischemia, the algorithm could
provide that a greater ST parameter change is required to trigger
diagnostic data collection, patient alert, or therapy.
[0163] Further, since many electrical axis shifts in the ECG may be
due to postural changes, the use of an accelerometers as have been
previously taught can detect postural changes. Therefore, the
accelerometer can be used as a redundant signal to verify that a
particular axis shift which is detected on the ECG corresponded
with a change in the patient posture.
[0164] Although an exemplary embodiment of the present invention
has been shown and described, it will be apparent to those having
ordinary skill in the art that a number of changes, modifications,
or alterations to the invention as described herein may be made,
none of which depart from the spirit of the present invention. All
such changes, modifications and alterations should therefore be
seen within the scope of the present invention.
* * * * *