U.S. patent application number 16/722399 was filed with the patent office on 2020-04-23 for rhythm discriminator with immunity to body posture.
The applicant listed for this patent is Medtronic, Inc.. Invention is credited to Robert W. STADLER, Xusheng ZHANG.
Application Number | 20200121212 16/722399 |
Document ID | / |
Family ID | 53488486 |
Filed Date | 2020-04-23 |
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United States Patent
Application |
20200121212 |
Kind Code |
A1 |
STADLER; Robert W. ; et
al. |
April 23, 2020 |
RHYTHM DISCRIMINATOR WITH IMMUNITY TO BODY POSTURE
Abstract
A medical device system includes a cardioverter-defibrillator
for detecting and treating ventricular tachycardia (VT). The
medical device system includes a sensing module for sensing a
cardiac signal from available cardiac signal sensing vectors. A
control module generates morphology templates of the cardiac
signals for multiple patient postures for each of the available
sensing vectors and determines a set of posture-independent
template features. An unknown cardiac rhythm is classified in
response to comparing features of a cardiac signal received during
the unknown rhythm to the set of posture-independent features.
Inventors: |
STADLER; Robert W.;
(Shoreview, MN) ; ZHANG; Xusheng; (Shoreview,
MN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Medtronic, Inc. |
Minneapolis |
MN |
US |
|
|
Family ID: |
53488486 |
Appl. No.: |
16/722399 |
Filed: |
December 20, 2019 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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15901935 |
Feb 22, 2018 |
10542901 |
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16722399 |
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14339789 |
Jul 24, 2014 |
9924885 |
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15901935 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61N 1/3624 20130101;
A61N 1/36535 20130101; A61B 5/1116 20130101; A61B 5/1118 20130101;
A61N 1/3622 20130101; A61N 1/3702 20130101; A61B 5/686 20130101;
A61N 1/36507 20130101; A61B 5/0472 20130101; A61N 1/3627 20130101;
A61N 1/3621 20130101; A61B 5/04525 20130101; A61B 5/0464 20130101;
A61N 1/36542 20130101; A61B 5/7207 20130101 |
International
Class: |
A61B 5/0452 20060101
A61B005/0452; A61N 1/362 20060101 A61N001/362; A61N 1/37 20060101
A61N001/37; A61N 1/365 20060101 A61N001/365; A61B 5/11 20060101
A61B005/11; A61B 5/0464 20060101 A61B005/0464 |
Claims
1. A medical device comprising: a sensing module coupled to a
plurality of electrodes defining a plurality of available sensing
vectors, the sensing module receiving cardiac signals using
selected ones of the available sensing vectors; and a control
module coupled to the sensing module and configured to: sense a
first cardiac signal during a known cardiac rhythm from each of the
plurality of available sensing vectors; for each of the plurality
of available sensing vectors, generate a plurality of morphology
templates of the first cardiac signal for each of a plurality of
patient postures; determine a set of template features from each of
the plurality of morphology templates; for each of the plurality of
available sensing vectors, compare the set of template features
from one of the plurality of morphology templates corresponding to
one of the plurality of postures to each of the sets of template
features from all of the other morphology templates corresponding
to all of the other of the plurality of postures; for each of the
plurality of available sensing vectors, store a set of
posture-independent template features in response to the comparing;
sense a second cardiac signal during an unknown cardiac rhythm from
at least one of the plurality of available sensing vectors;
determine features from the second cardiac signal that are
analogous to the set of posture-independent template features
stored for the at least one of the plurality of available sensing
vectors; compare the features determined from the second cardiac
signal to the analogous set of posture-independent template
features; and classify the unknown cardiac rhythm based on at least
the comparison.
2. The device of claim 1, wherein the control module is configured
to classify the unknown cardiac rhythm by: selecting at least two
of the available sensing vectors; classifying each of the at least
two of the available sensing vectors as one of ventricular
tachycardia and supraventricular tachycardia based on at least the
comparison of the features determined from the second cardiac
signal to the set of posture-independent templates for the
respective sensing vector; and classifying the unknown cardiac
rhythm as supraventricular tachycardia in response to at least one
of the selected sensing vectors being classified as
supraventricular tachycardia.
3. The device of claim 1, wherein the control module is further
configured to: produce a supraventricular tachycardia
classification region of an n-dimensional space defined by the set
of posture-independent features for a respective one of the
available sensing vectors; wherein comparing the features
determined from the cardiac signal to the set of
posture-independent templates comprises determining if the features
define a point within the supraventricular tachycardia
classification region.
4. The device of claim 1, wherein the control module is further
configured to: determine each set of posture-independent features
as a posture-independent set of coordinates in an n-dimensional
space, the set of coordinates comprising a value of each
posture-independent feature included in a respective set of
posture-independent features, wherein the n-dimensional space
comprises a dimension corresponding to each posture-independent
feature included in the set of posture-independent features;
determine the features from the second cardiac signal as a cardiac
signal set of coordinates in the n-dimensional space; determine a
distance between the cardiac signal set of coordinates and the
posture-independent set of coordinates; and classify the unknown
cardiac rhythm based on the determined distance.
5. The device of claim 4, wherein the control module is further
configured to: compare the distance to a supraventricular
tachycardia classification threshold; and classify the unknown
cardiac rhythm as supraventricular tachycardia in response to the
distance being less than the threshold.
6. The device of claim 1, wherein the control module is further
configured to determine features from each one of a plurality of
cardiac cycles from the second cardiac signal that are analogous to
the set of posture-independent template features stored for the at
least one of the plurality of available sensing vectors; compare
the features determined from each one of the plurality of cardiac
cycles to the analogous set of posture-independent template
features; classify the at least one of the plurality of available
sensing vectors in response to a threshold number of the plurality
cardiac cycles matching the analogous set of posture-independent
template features; and classify the unknown cardiac rhythm based on
the classification of the at least one of the plurality of
available sensing vectors.
7. The device of claim 1, wherein the control module is further
configured to determine the features of the second cardiac signal
by: determining an average cardiac cycle signal from a plurality of
cardiac cycles of the second cardiac signal; and determining the
features of the cardiac signal from the averaged cardiac cycle.
8. The device of claim 1, wherein the control module is further
configured to classify the unknown cardiac rhythm as one of
supraventricular tachycardia and ventricular tachycardia.
9. The device of claim 8, wherein the control module is further
configured to classify the unknown cardiac rhythm as
supraventricular tachycardia in response to at least one feature of
the second cardiac signal matching an analogous feature of the set
of posture-independent features within a predetermined match
threshold.
10. The device of claim 8, further comprising a therapy delivery
module coupled to the plurality of electrodes for delivering a
tachycardia therapy; wherein the control module is configured to
withhold a ventricular tachycardia therapy in response to
classifying the unknown cardiac rhythm as a supraventricular
tachycardia.
11. The device of claim 10, wherein the control module is further
configured to classify the unknown cardiac rhythm as ventricular
tachycardia in response to none of the features of the second
cardiac signal matching the analogous feature of the set of
posture-independent features within the predetermined match
threshold, and the therapy delivery module provides a ventricular
tachycardia therapy in response to classifying the unknown cardiac
rhythm as ventricular tachycardia.
12. The device of claim 11, wherein the ventricular tachycardia
therapy comprises one of anti-tachycardia pacing (ATP) or shock
therapy.
13. The device of claim 1, further comprising a therapy delivery
module coupled to the plurality of electrodes for delivering a
tachycardia therapy; wherein the control module is configured to
classify the unknown cardiac rhythm as ventricular tachycardia and
control the therapy delivery module to provide a ventricular
tachycardia therapy in response to classifying the unknown cardiac
rhythm as ventricular tachycardia.
14. The device of claim 13, wherein the ventricular tachycardia
therapy comprises one of anti-tachycardia pacing (ATP) or shock
therapy.
15. The device of claim 13, wherein the control module is
configured to classify the unknown cardiac rhythm as ventricular
tachycardia in response to none of the features of the second
cardiac signal matching an analogous feature of the set of
posture-independent features within a predetermined match
threshold.
16. The device of claim 1, further comprising a therapy delivery
module coupled to the plurality of electrodes for delivering a
tachycardia therapy, wherein the control module is further
configured to obtain R-R time intervals measured between
consecutive ventricular events, detect ventricular tachycardia
within the unknown cardiac rhythm based on at least the R-R time
intervals, and, after detecting ventricular tachycardia based on at
least the R-R time intervals: determine the features from the
second cardiac signal that are analogous to the set of
posture-independent template features stored for the at least one
of the plurality of available sensing vectors; compare the features
determined from the second cardiac signal to the analogous set of
posture-independent template features; classify the ventricular
tachycardia as supraventricular tachycardia based on at least the
comparison; and withhold a ventricular tachycardia therapy in
response to classifying the ventricular tachycardia as
supraventricular tachycardia.
17. A non-transitory, computer-readable medium storing a set of
instructions which, when executed by a control module of an
implantable medical device, cause the implantable medical device
to: sense a first cardiac signal during a known cardiac rhythm from
each of the plurality of available sensing vectors; for each of the
plurality of available sensing vectors, generate a plurality of
morphology templates of the first cardiac signal for each of a
plurality of patient postures; determine a set of template features
from each of the plurality of morphology templates; for each of the
plurality of available sensing vectors, compare the set of template
features from one of the plurality of morphology templates
corresponding to one of the plurality of postures to each of the
sets of template features from all of the other morphology
templates corresponding to all of the other of the plurality of
postures; for each of the plurality of available sensing vectors,
store a set of posture-independent template features in response to
the comparing; sense a second cardiac signal during an unknown
cardiac rhythm from at least one of the plurality of available
sensing vectors; determine features from the second cardiac signal
that are analogous to the set of posture-independent template
features stored for the at least one of the plurality of available
sensing vectors; compare the features determined from the second
cardiac signal to the analogous set of posture-independent template
features; and classify the unknown cardiac rhythm in response to
comparing the features determined from the second cardiac signal to
the analogous set of posture-independent template features.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of U.S. patent
application Ser. No. 15/901,935, filed Feb. 22, 2018 (published as
U.S. Publication No. 2018/0177425), which was a continuation of
U.S. patent application Ser. No. 14/339,789 (granted as U.S. Pat.
No. 9,924,885) filed Jul. 24, 2014, the entire content of both of
which are incorporated herein by reference in their entirety.
TECHNICAL FIELD
[0002] The disclosure relates generally to medical devices and, in
particular, to a method and apparatus for discriminating
supraventricular tachycardia (SVT) from ventricular tachycardia
(VT) when cardiac signal morphology changes with patient body
posture.
BACKGROUND
[0003] A variety of implantable medical devices (IMDs) for
delivering a therapy, monitoring a physiological condition of a
patient or a combination thereof have been clinically implanted or
proposed for clinical implantation in patients. Some IMDs may
employ one or more elongated electrical leads carrying stimulation
electrodes, sense electrodes, and/or other sensors. IMDs may
deliver therapy to or monitor conditions of a variety of organs,
nerves, muscle or tissue, such as the heart, brain, stomach, spinal
cord, pelvic floor, or the like. Implantable medical leads may be
configured to allow electrodes or other sensors to be positioned at
desired locations for delivery of electrical stimulation or sensing
of physiological conditions. For example, electrodes or sensors may
be carried at a distal portion of a lead. A proximal portion of the
lead may be coupled to an implantable medical device housing, which
may contain circuitry such as signal generation circuitry and/or
sensing circuitry.
[0004] Some IMDs, such as cardiac pacemakers or implantable
cardioverter defibrillators (ICDs), provide therapeutic electrical
stimulation to or monitor the heart of the patient via electrodes
carried by one or more implantable leads. The leads may be
transvenous, i.e., implanted in the heart through one or more
veins, sometimes referred to as endocardial leads. Other leads may
be non-transvenous leads implanted outside the heart. In either
case, the electrical stimulation provided by the IMD may include
signals such as pacing pulses, cardioversion shocks or
defibrillation shocks to address abnormal cardiac rhythms such as
bradycardia, tachycardia or fibrillation.
[0005] In some cases, the IMD senses signals representative of
intrinsic depolarizations of the heart and analyzes the sensed
signals to identify normal or abnormal rhythms. Upon detection of
an abnormal rhythm, the device may deliver an appropriate
electrical stimulation signal or signals to restore or maintain a
more normal rhythm. For example, an IMD may deliver pacing pulses
to the heart upon detecting tachycardia or bradycardia, and deliver
cardioversion or defibrillation shocks to the heart upon detecting
tachycardia or fibrillation.
SUMMARY
[0006] In general, the disclosure is directed to techniques for
discriminating between treatable heart rhythms, e.g., ventricular
tachycardia (VT), and non-treatable heart rhythms, e.g.,
supra-ventricular tachycardia (SVT), of a heart of a patient. An
ICD operating in accordance with the techniques performs a
morphology analysis for detecting and discriminating VT and SVT
based on posture-independent cardiac signal template features.
[0007] To reduce the likelihood of misclassification of the rhythm,
the ICD generates and stores cardiac electrical signal templates
for multiple patient body postures for all available cardiac signal
sensing vectors. For each sensing vector the ICD extracts
posture-independent features from the templates. In one example,
the ICD compares analogous features of a cardiac electrical signal
sensed during an unknown rhythm to at least a portion of the stored
features. The ICD classifies the unknown rhythm as VT or SVT based
on the comparison.
[0008] In one example, the disclosure provides a method comprising
sensing a first cardiac signal during a known cardiac rhythm from
each of a plurality of available sensing vectors; for each of the
available sensing vectors, generating a plurality of morphology
templates of the first cardiac signal for each of a plurality of
patient postures; determining a set of template features from each
of the plurality of morphology templates; for each of the plurality
of available sensing vectors, comparing the set of template
features from one of the plurality of morphology templates
corresponding to one of the plurality of postures to each of the
sets of template features from all of the other morphology
templates corresponding to all of the other of the plurality of
postures; for each of the plurality of available sensing vectors,
storing a set of posture-independent template features in response
to the comparing; sensing a second cardiac signal during an unknown
cardiac rhythm from at least one of the plurality of available
sensing vectors; determining features from the second cardiac
signal that are analogous to the set of posture-independent
template features stored for the at least one of the plurality of
available sensing vectors; comparing the features determined from
the second cardiac signal to the analogous set of
posture-independent template features; and classifying the unknown
cardiac rhythm in response to comparing the features determined
from the second cardiac signal to the analogous set of
posture-independent template features.
[0009] In another example, the disclosure provides an implantable
medical device (IMD) comprising a sensing module coupled to a
plurality of electrodes defining a plurality of available sensing
vectors and a control module coupled to the sensing module. The
control module is configured to sense a first cardiac signal during
a known cardiac rhythm from each of the plurality of available
sensing vectors and, for each of the plurality of available sensing
vectors, generate a plurality of morphology templates of the first
cardiac signal for each of a plurality of patient postures and
determine a set of template features from each of the plurality of
morphology templates. For each of the plurality of available
sensing vectors, the control module is further configured to
compare the set of template features from one of the plurality of
morphology templates corresponding to one of the plurality of
postures to each of the sets of template features from all of the
other morphology templates corresponding to all of the other of the
plurality of postures and store a set of posture-independent
template features in response to the comparing. The control module
senses a second cardiac signal during an unknown cardiac rhythm
from at least one of the plurality of available sensing vectors,
determines features from the second cardiac signal that are
analogous to the set of posture-independent template features
stored for the at least one of the plurality of available sensing
vectors, compares the features determined from the second cardiac
signal to the analogous set of posture-independent template
features; and classifies the unknown cardiac rhythm in response to
comparing the features determined from the second cardiac signal to
the analogous set of posture-independent template features.
[0010] In another example, the disclosure provides a
computer-readable storage medium comprising instructions which,
when executed by a control module in an implantable medical device,
cause the implantable medical device to sense a first cardiac
signal during a known cardiac rhythm from each of the plurality of
available sensing vectors; for each of the plurality of available
sensing vectors, generate a plurality of morphology templates of
the first cardiac signal for each of a plurality of patient
postures; determine a set of template features from each of the
plurality of morphology templates; for each of the plurality of
available sensing vectors, compare the set of template features
from one of the plurality of morphology templates corresponding to
one of the plurality of postures to each of the sets of template
features from all of the other morphology templates corresponding
to all of the other of the plurality of postures; for each of the
plurality of available sensing vectors, store a set of
posture-independent template features in response to the comparing;
sense a second cardiac signal during an unknown cardiac rhythm from
at least one of the plurality of available sensing vectors;
determine features from the second cardiac signal that are
analogous to the set of posture-independent template features
stored for the at least one of the plurality of available sensing
vectors; compare the features determined from the second cardiac
signal to the analogous set of posture-independent template
features; and classify the unknown cardiac rhythm in response to
comparing the features determined from the second cardiac signal to
the analogous set of posture-independent template features.
[0011] This summary is intended to provide an overview of the
subject matter described in this disclosure. It is not intended to
provide an exclusive or exhaustive explanation of the apparatus and
methods described in detail within the accompanying drawings and
description below. Further details of one or more examples are set
forth in the accompanying drawings and the description below.
BRIEF DESCRIPTION OF THE DRAWINGS
[0012] FIG. 1 is a conceptual diagram of a patient implanted with
an example IMD system that includes an ICD coupled to a
subcutaneous defibrillation lead.
[0013] FIG. 2 is a transverse view of the patient in FIG. 1
depicting the defibrillation lead implanted in an alternate
location.
[0014] FIG. 3 is a schematic diagram of an ICD according to one
embodiment.
[0015] FIG. 4 is a flow chart of a method performed by an ICD for
generating morphology templates and extracting posture-independent
discrimination features for detecting and classifying VT and
SVT.
[0016] FIG. 5 is a flow chart of a method for discriminating
between VT and SVT according to one example.
[0017] FIG. 6 is a multi-dimensional plot of posture-independent
features depicting an SVT classification region.
[0018] FIG. 7 is a flow chart of a method for performing VT
detection according to another example.
DETAILED DESCRIPTION
[0019] In general, this disclosure describes techniques for
distinguishing between treatable arrhythmias and non-treatable
arrhythmias. Treatable arrhythmias refer to abnormal heart rhythms
for which stimulation therapy is delivered to one or both of the
ventricles. Treatable arrhythmias may include ventricular
tachycardia (VT) or ventricular fibrillation (VF). Treatable
arrhythmias generally pose an immediate danger to the patient and
therapy is needed in order to ensure the safety of the patient.
Non-treatable arrhythmias, on the other hand, refer to abnormal
heart rhythms that typically do not require stimulation therapy to
be delivered to either of the ventricles. Non-treatable arrhythmias
may include supra-ventricular tachycardia (SVT), which includes
sinus tachycardia, atrial tachycardia (AT), atrial fibrillation
(AF), atrial flutter, atrioventricular nodal reentrant tachycardia
(AVNRT), atrioventricular reciprocating tachycardia (AVRT), or the
like. Non-treatable arrhythmias do not generally pose an immediate
danger to the patient. As such, non-treatable arrhythmias may go
untreated, i.e., no stimulation therapy is delivered to the heart.
In other instances, non-treatable arrhythmias may be treated using
stimulation therapy, but the stimulation therapy is not delivered
to the ventricles of the patient.
[0020] Accurately determining whether the heart rhythm is treatable
or non-treatable prevents inadvertent delivery of therapy to a
ventricle of the patient when no therapy to the ventricle is
necessary (e.g., in the case of a rhythm mischaracterized as a
treatable arrhythmia) or withholding stimulation therapy when the
therapy to the ventricle is necessary (e.g., in the case of a
rhythm mischaracterized as a non-treatable arrhythmia). Unnecessary
delivery of stimulation therapy to the patient may be uncomfortable
for the patient, needlessly depletes the power source of the
medical device and, in some patients or circumstances, can induce
more dangerous arrhythmias.
[0021] Some ICD systems rely on electrodes that are implanted
outside the heart for receiving electrocardiogram (ECG) signals
that are used to detect and discriminate heart rhythms. These ICD
systems may be desirable for some patients because the elimination
of transvenous leads eliminates the need to advance catheters and
leads into the blood vessels and heart of the patient and reduces
the risk of serious infection by eliminating the pathway for
infection from a subcutaneous pocket to the patient's heart. The
ECG is sensed from electrodes implanted outside the cardiovascular
system, for example subcutaneously, submuscularly, or substernally,
in some examples. The ECG obtained from electrodes implanted
outside the cardiovascular system may be subject to morphology
changes due to changes in patient posture.
[0022] An ICD according to the present disclosure includes a
tachyarrhythmia detector for discriminating between VT and SVT
using ECG morphology analysis. The ECG is sensed from electrodes
implanted outside the cardiovascular system, for example
subcutaneously, submuscularly or substernally. The ECG obtained
from electrodes implanted outside the cardiovascular system may be
subject to morphology changes due to changes in patient posture.
The tachyarrhythmia detector is configured to analyze the ECG
acquired during different patient postures to generate a set of ECG
signal features that are substantially insensitive to changes in
patient posture but highly discriminative for detecting VT and SVT.
The tachyarrhythmia detector performs a comparative morphology
analysis that utilizes the ECG features previously identified as
being substantially immune to patient posture changes but reliable
for discriminating between VT and SVT.
[0023] FIG. 1 is a conceptual diagram of a patient 12 implanted
with an example IMD system 10 that includes an ICD 14 coupled to a
defibrillation lead 16. Defibrillation lead 16 includes a proximal
end that is connected to ICD 14 and a distal end that includes one
or more electrodes. Defibrillation lead 16 is illustrated in FIG. 1
as being implanted subcutaneously, e.g., in tissue and/or muscle
between the skin and the ribcage 32 and/or sternum 22.
Defibrillation lead 16 extends subcutaneously from ICD 14 toward
xiphoid process 20. At a location near xiphoid process 20
defibrillation lead 16 bends or turns and extends subcutaneously
superior, substantially parallel to sternum 22. Although
illustrated as being offset laterally from and extending
substantially parallel to sternum 22 in the example of FIG. 1,
defibrillation lead 16 may be implanted over sternum 22, offset
from sternum 22, but not parallel to sternum 22 (e.g., angled
laterally from sternum 22 at either the proximal or distal
end).
[0024] In other instances, lead 16 may be implanted at other
extravascular locations. As shown in a transverse view of patient
12 in FIG. 2, lead 16 may be implanted at least partially in a
substernal location, e.g., between the ribcage 32 and/or sternum 22
and heart 26. In one such configuration, a proximal portion of lead
16 extends subcutaneously from ICD 14 toward sternum 22 (not seen
in the transverse view of FIG. 2) and a distal portion of lead 16
extends superior under or below the sternum 22 in the anterior
mediastinum 36. Anterior mediastinum 36 is bounded laterally by
pleurae 39, posteriorly by pericardium 38, and anteriorly by
sternum 22.
[0025] In some instances, the anterior wall of anterior mediastinum
36 may also be formed by the transversus thoracis and one or more
costal cartilages. Anterior mediastinum 36 includes a quantity of
loose connective tissue (such as areolar tissue), some lymph
vessels, lymph glands, substernal musculature (e.g., transverse
thoracic muscle), branches of the internal thoracic artery, and the
internal thoracic vein. In one example, the distal portion of lead
16 extends along the posterior side of sternum 22 substantially
within the loose connective tissue and/or substernal musculature of
anterior mediastinum 36. Lead 16 may be at least partially
implanted in other intrathoracic locations, e.g., other
non-vascular, extra-pericardial locations, including the gap,
tissue, or other anatomical features around the perimeter of and
adjacent to, but not attached to, the pericardium or other portion
of heart 26 and not above sternum 22 or ribcage 32.
[0026] In another example, ICD 14 may be implanted subcutaneously
outside the ribcage 32 in an anterior medial location. Lead 16 may
be tunneled subcutaneously into a location adjacent to a portion of
the latissimus dorsi muscle of patient 12, from a medial implant
pocket of ICD 14 laterally and posterially to the patient's back to
a location opposite heart 26 such that the heart 26 is generally
disposed between the ICD 14 and distal electrode coil 24 and distal
sensing electrode 28.
[0027] Referring again to FIG. 1, defibrillation lead 16 includes
an elongated lead body 18 carrying electrodes 24, 28 and 30 located
along the distal portion of the length of the lead body 18. Lead
body 18 insulates one or more elongated electrical conductors (not
illustrated) that extend from a respective electrode 24, 28 and 30
through the lead body to a proximal connector (not shown) that is
coupled to ICD 14. Lead body 16 may be formed from a non-conductive
material, such as silicone, polyurethane, fluoropolymers, or
mixtures thereof or other appropriate materials, and is shaped to
form one or more lumens within which the one or more conductors
extend. The conductors are electrically coupled to ICD circuitry,
such as a therapy module or a sensing module, via connections in an
ICD connector assembly 17 that includes a connector bore for
receiving the proximal connector of lead 16 and associated
electrical feedthroughs crossing ICD housing 15. The electrical
conductors transmit therapy from a therapy module within ICD 14 to
one or more of electrodes 24, 28, and 30, and transmit sensed
electrical signals from one or more of electrodes 24, 28, and 30 to
the sensing module within ICD 14.
[0028] Defibrillation lead 16 is shown in FIG. 1 to include a
defibrillation electrode 24, which may be an elongated coil
electrode, along the distal portion of defibrillation lead 16.
Defibrillation lead 16 is located on lead 16 such that when ICD
system 10 is implanted a therapy vector between defibrillation
electrode 24 and a housing or can electrode 15 of ICD 14 is
substantially through or across the ventricle(s) of heart 26.
[0029] Defibrillation lead 16 also includes one or more sensing
electrodes 28 and 30, located toward the distal portion of
defibrillation lead 16. In the example illustrated in FIG. 1,
sensing electrodes 28 and 30 are separated from one another by
defibrillation electrode 24. In other words, sensing electrode 28
is located distal to defibrillation electrode 24 and sensing
electrode 30 is proximal to defibrillation electrode 24. ICD system
10 may sense electrical activity of heart 26 via one or more of
sensing vectors that include combinations of electrodes 28 and 30
and the housing or can electrode 15 of ICD 14. For example, ICD 14
may receive a subcutaneous ECG signal across a sensing vector
between electrodes 28 and 30, a sensing vector between electrode 28
and the conductive housing or can electrode 15, a sensing vector
between electrode 30 and the conductive housing or can electrode
15, or any combination of electrodes 28, 30 and the housing or can
electrode 15. In some instances, ICD 14 may even sense cardiac
electrical signals using a sensing vector that includes
defibrillation electrode 24.
[0030] ICD 14 receives cardiac electrical signals from one or more
of the sensing vectors described above for detecting
tachyarrhythmias. ICD 14 may deliver one or more cardioversion or
defibrillation shocks via defibrillation electrode 24 in response
to detecting VT or VF. ICD 14 may also provide pacing therapy, such
as anti-tachycardia pacing (ATP) and/or post-shock pacing after a
cardioversion or defibrillation shock when pacing capabilities are
available.
[0031] ICD 14 includes a housing 15, also referred to herein as
housing electrode or can electrode 15, which forms a hermetic seal
that protects internal electronic components of ICD 14. The housing
15 may be formed of a conductive material, such as titanium,
titanium alloy, or other conductive material, to serve as an
electrode. Housing 15 may function as a "can electrode" since the
conductive housing or a portion thereof may be coupled to internal
circuitry to be used as an indifferent or ground electrode during
sensing or defibrillation shock delivery.
[0032] ICD 14 also includes connector assembly 17 (also referred to
as a connector block or header) that includes electrical
feedthroughs through which electrical connections are made between
electrical conductors within lead 16 and electronic components
included within the housing 15. As will be described in further
detail herein, housing 15 may enclose one or more processors,
memory devices, transmitters, receivers, sensors, sensing
circuitry, therapy circuitry and other appropriate components.
[0033] The example shown in FIG. 1 is illustrative in nature and
should not be considered limiting of the techniques described in
this disclosure. In other examples, ICD 14 and one or more
associated leads may be implanted at other locations. For example,
ICD 14 may be implanted in a subcutaneous pocket in the right
chest. In this example, defibrillation lead 16 may extend
subcutaneously from the device toward the manubrium of the sternum
22 and bend or turn and extend subcutaneously or substernally
inferiorly from the manubrium of the sternum, substantially
parallel with the sternum.
[0034] The techniques disclosed herein may be implemented in
numerous ICD and electrode configurations that include one or more
housing-based electrodes and/or one or more lead-based electrodes
for enabling sensing of an ECG signal across one or more sensing
vectors and for delivering electrical stimulation therapies to
heart 26. The IMD system 10 is an extravascular IMD system because
lead 16 is positioned in an extravascular location outside the
blood vessels, heart 26 and pericardium 38. It is understood that
while ICD 14 and lead 16 may be positioned between the skin and a
muscle layer of the patient 12, ICD 14 and any associated leads
could be positioned in any extravascular location of the patient,
such as below a muscle layer or even within the thoracic
cavity.
[0035] An external device 40 is shown in telemetric communication
with ICD 14 by a communication link 42. External device 40 may
include a processor 52, display 54, user interface 56 and telemetry
unit 58. Processor 52 controls external device operations and
processes data and signals received from ICD 14. Display 54, which
may include a graphical user interface, displays data and other
information to a user for reviewing ICD operation and programmed
parameters as well as ECG signals retrieved from ICD 14. User
interface 56 may include a mouse, touch screen, key pad or the like
to enable a user to interact with external device 40 to initiate a
telemetry session with ICD 14 for retrieving data from and/or
transmitting data to ICD 14. Telemetry unit 58 is configured for
bidirectional communication with a telemetry module included in ICD
14 and is configured to operate in conjunction with processor 52
for sending and receiving data relating to ICD functions via
communication link 42.
[0036] Communication link 42 may be established between ICD 14 and
external device 40 using a radio frequency (RF) link such as
Bluetooth, Wi-Fi, or Medical Implant Communication Service (MICS)
or other RF bandwidth. External device 40 may be embodied as a
programmer used in a hospital, clinic or physician's office to
retrieve data from ICD 14 and to program operating parameters and
algorithms in ICD 14 for controlling ICD 14 functions. For example,
external device 40 may be used to program ICD tachyarrhythmia
detection parameters, such as VT and VF interval zones, VT and VF
NID, and detection thresholds relating to morphology analysis of
the ECG signals. External device 40 may also be used to program
therapy control parameters, such as the shock energy used to
terminate VT or VF. External device 40 may alternatively be
embodied as a home monitor or handheld device.
[0037] The tachycardia discrimination and therapy delivery
techniques disclosed herein are useful in an extravascular IMD
system such as the system 10 shown in FIG. 1 that may be
susceptible to posture-induced ECG morphology changes. Sensing
electrodes 28 and 30 carried by lead 16 and located in subcutaneous
or substernal locations may be more susceptible to posture-induced
changes in the cardiac signal morphology than sensing electrodes
attached to or within the heart. An extravascular IMD system is
less invasive and may be more easily implanted than a system
including transvenous or epicardial leads. However, techniques
disclosed herein may be implemented in other examples of IMD
systems that include transvenous intracardiac leads and electrodes,
epicardial electrodes or other lead and electrode systems. Examples
of other IMD systems in which the techniques disclosed herein could
be implemented for discriminating VT from SVT in the presence of
posture-induced cardiac signal morphology changes are generally
disclosed in U.S. Pat. No. 7,031,771 (Brown et al.) and U.S. Pat.
No. 5,447,519 (Peterson), and U.S. Pat. No. 7,496,409 (Greenhut, et
al.) all of which patents are incorporated herein by reference in
their entirety.
[0038] FIG. 3 is a schematic diagram of ICD 14 according to one
embodiment. The electronic circuitry enclosed within housing 15
includes software, firmware and hardware that cooperatively monitor
one or more ECG signals, determine when a
cardioversion-defibrillation shock is necessary, and deliver
prescribed cardioversion-defibrillation therapies. In some
examples, ICD 14 may be coupled to a lead, such as lead 16,
carrying electrodes, such as electrodes 24, 28 and 30, positioned
in operative relation to the patient's heart for delivering cardiac
pacing pulses and may therefore include the capability to deliver
low voltage pacing pulses as well as the high voltage shock
pulses.
[0039] ICD 14 includes control module 80, associated memory 82,
therapy delivery module 84, electrical sensing module 86, telemetry
module 88, and cardiac signal analyzer 90. A power source 98
provides power to the circuitry of ICD 14, including each of the
modules 80, 82, 84, 86, 88, and 90 as needed. Power source 98 may
include one or more energy storage devices, such as one or more
rechargeable or non-rechargeable batteries.
[0040] The functional blocks shown in FIG. 3 represent
functionality that may be included in ICD 14 and may include any
discrete and/or integrated electronic circuit components that
implement analog and/or digital circuits capable of producing the
functions attributed to ICD 14 herein. For example, the modules may
include analog circuits, e.g., amplification circuits, filtering
circuits, and/or other signal conditioning circuits. The modules
may also include digital circuits, e.g., analog-to-digital
converters, combinational or sequential logic circuits, integrated
circuits, processors, ASICs, memory devices, etc.
[0041] Memory 82 may include any volatile, non-volatile, magnetic,
or electrical non-transitory computer readable storage media, such
as a random access memory (RAM), read-only memory (ROM),
non-volatile RAM (NVRAM), electrically-erasable programmable ROM
(EEPROM), flash memory, or any other memory device. Furthermore,
memory 82 may include non-transitory computer readable media
storing instructions that, when executed by one or more processing
circuits, cause control module 80 or other ICD modules to perform
various functions attributed to ICD 14. The non-transitory computer
readable media storing the instructions may include any of the
media listed above, with the sole exception being a transitory
propagating signal.
[0042] The functions attributed to the modules herein may be
embodied as one or more processors, hardware, firmware, software,
or any combination thereof. Depiction of different features as
modules is intended to highlight different functional aspects and
does not necessarily imply that such modules must be realized by
separate hardware or software components. Rather, functionality
associated with one or more modules may be performed by separate
hardware or software components, or integrated within common
hardware or software components. For example, arrhythmia detection
operations performed by cardiac signal analyzer 90 for determining
a need for therapy delivered by ICD 14 may be implemented in
control module 80 executing instructions stored in memory 82. As
used herein, the term "module" refers to an application specific
integrated circuit (ASIC), an electronic circuit, a processor
(shared, dedicated, or group) and memory that execute one or more
software or firmware programs, a combinational logic circuit, state
machine, or other suitable components that provide the described
functionality.
[0043] Control module 80 communicates with therapy delivery module
84, cardiac signal analyzer 90 and electrical sensing module 86 for
sensing cardiac electrical activity, detecting cardiac rhythms, and
generating cardiac therapies in response to sensed signals. Therapy
delivery module 84 and electrical sensing module 86 are
electrically coupled to electrodes 24, 28, and 30 carried by lead
16 (shown in FIG. 1) and housing electrode 15, which may serve as a
common or ground electrode.
[0044] Electrical sensing module 86 is selectively coupled to
electrodes 28, 30 and housing electrode 15 in order to monitor
electrical activity of the patient's heart. Electrical sensing
module 86 may additionally be selectively coupled to electrode 24.
Sensing module 86 is enabled to selectively monitor one or more
sensing vectors selected from the available electrodes 24, 28, 30
and 15. For example, sensing module 86 may include switching
circuitry for selecting which of electrodes 24, 28, 30 and housing
electrode 15 are coupled to sense amplifiers included in sensing
module 86. Switching circuitry may include a switch array, switch
matrix, multiplexer, or any other type of switching device suitable
to selectively couple sense amplifiers to selected electrodes.
[0045] In some examples, electrical sensing module 86 includes
multiple sensing channels for sensing multiple ECG sensing vectors
selected from electrodes 24, 28, 30 and housing electrode 15. For
example, a sensing vector between electrodes 28 and 30 may be
selected for sensing a first ECG vector on one channel and at least
one additional sensing vector may be selected between one of
electrodes 24, 28 and 30 paired with the housing electrode 15 and
received on another sensing channel. Each sensing channel may be
configured to amplify and filter the ECG to improve the signal
quality for sensing cardiac events, e.g., R-waves.
[0046] Each sensing channel of sensing module 86 includes a sense
amplifier for receiving the ECG signals developed across the
selected electrodes. The sense amplifiers pass sense event signals
to control module 80 and/or cardiac signal analyzer 90. For example
R-wave sense signals may be passed to tachyarrhythmia detector 94
and timing circuit 92 of cardiac signal analyzer 90 when a received
ECG signal crosses a sensing threshold, which may be an
auto-adjusting sensing threshold in some instances.
[0047] Sensing module 86 may include an analog-to-digital converter
for providing a digital ECG signal to control module 80 and/or
cardiac signal analyzer 90. In one example, two sensing channels
are provided for receiving an ECG from a first sensing vector
between electrodes 28 and 30 and a second sensing vector selected
from either electrode 28 or electrode 30 paired with the housing
electrode 15. The two ECG signals are converted to a multi-bit
digital signal by sensing module 86 and provided to tachyarrhythmia
detector 94 for performing ECG morphology analysis as described
herein.
[0048] Cardiac signal analyzer 90 includes a tachyarrhythmia
detector 94 for detecting and discriminating SVT, VT and VF and
timing circuit 92. Timing circuit 92 may include various timers
and/or counters for measuring time intervals, such as RR intervals,
and setting time windows such as morphology template windows or
morphology analysis windows relative to R-wave sense signals or for
performing other timing related functions of cardiac signal
analyzer 90.
[0049] The timing of R-wave sense signals received from sensing
module 86 is used by timing circuit 94 to measure RR intervals.
Tachyarrhythmia detector 94 may count RR intervals measured by
timing circuit 92 that fall into different rate detection zones for
determining a ventricular rate or preforming other rate- or
interval-based assessment for detecting ventricular
tachyarrhythmia.
[0050] Tachyarrhythmia detector 94 receives digitized ECG signals
from cardiac signal analyzer 90 for use in detecting
tachyarrhythmia based on signal morphology. Examples of algorithms
that may be performed by ICD 14 for detecting, discriminating and
treating tachyarrhythmia and adapted to include techniques
described herein are generally disclosed in U.S. Pat. No. 5,354,316
(Keimel); U.S. Pat. No. 5,545,186 (Olson, et al.); U.S. Pat. No.
6,393,316 (Gillberg et al.); U.S. Pat. No. 7,031,771 (Brown, et
al.); U.S. Pat. No. 8,160,684 (Ghanem, et al.), and U.S. Pat. No.
8,437,842 (Zhang, et al.), all of which patents are incorporated
herein by reference in their entirety.
[0051] The detection algorithm is highly sensitive and specific for
the presence or absence of life threatening VT and VF. Therapy
delivery module 84 includes a high voltage (HV) therapy delivery
module including one or more HV output capacitors and, in some
instances, a low voltage therapy delivery module. When a malignant
tachycardia is detected the HV capacitors are charged to a
pre-programmed voltage level by a HV charging circuit. Control
module 80 applies a signal to trigger discharge of the HV
capacitors upon detecting a feedback signal from therapy delivery
module 84 that the HV capacitors have reached the voltage required
to deliver a programmed shock energy. In this way, control module
80 controls operation of the high voltage output circuit of therapy
delivery module 84 to deliver high energy
cardioversion/defibrillation shocks using defibrillation electrode
24 and housing electrode 15. Timing circuit 92 may be used to
control R-wave synchronized shock pulses delivered by therapy
delivery module 84.
[0052] It should be noted that implemented arrhythmia detection
algorithms may utilize not only ECG signal analysis methods but may
also utilize supplemental sensors 96, such as blood pressure,
tissue oxygenation, respiration, patient activity, heart sounds,
and the like, for contributing to a decision by control module 80
to apply or withhold a therapy.
[0053] Certain steps in the performance of the VT detection
algorithm described herein are cooperatively performed in control
module 80, including memory 82, cardiac signal analyzer 90 and
stored detection criteria and other control parameters that may be
programmed into memory 82 via telemetry module 88. Initial
detection of VT or VF may be determined in the tachyarrhythmia
detector 94 as a function of the time intervals between R-wave
sense event signals that are output from sensing module 86.
Discrimination of VT and SVT is performed by tachyarrhythmia
detector 94 through analysis of the morphology of the sensed ECG
signal(s) after an initial RR interval-based VT detection is made
in some examples. Digital ECG signals received from one or more
sensing channels of sensing module 86 may be stored in memory 82.
Tachyarrhythmia detector 94 employs the digitized ECG signals
stored in memory 82 in conjunction with morphology analysis.
[0054] As described below, digitized ECG signals are acquired
during a stable heart rhythm (stable rate and morphology) and used
by cardiac signal analyzer 90 to generate morphology templates for
each available sensing vector, for example three vectors between
electrodes 28 and 30, between electrode 28 and housing electrode
15, and between electrode 30 and housing electrode 15,
respectively. A morphology template for each sensing vector is
generated for multiple patient postures.
[0055] Morphology analysis performed by tachyarrhythmia detector 94
includes comparing one or more ECG signals sensed using selected
sensing vectors during an unknown heart rhythm to morphology
templates stored in memory 82 for the respective sensing vector. As
indicated above, the unknown heart rhythm may be preliminarily
detected as VT according to rate-based RR interval detection
criteria using R-wave sense signals produced in response to one or
more selected ECG signals. Some aspects of sensing and processing
subcutaneous ECG signals are generally disclosed in
commonly-assigned U.S. Pat. No. 7,904,153 (Greenhut, et al.),
hereby incorporated herein by reference in its entirety.
[0056] A morphology template is generated for each available
sensing vector for at least two different patient postures, for
example sitting and lying. A morphology template may be an ensemble
averaged waveform obtained from a predetermined number of cardiac
cycles. A template window may be defined relative to R-wave sense
signals produced by electrical sensing module 86. The ECG signal
may be ensemble averaged across multiple template windows to obtain
a waveform template for a given sensing vector and patient posture.
Morphology templates may be updated periodically. Methods for
generating and updating a morphology template and template
comparisons performed by ICD 14 may include techniques generally
disclosed in U.S. Pat. No. 6,745,068 (Koyrakh, et al.). U.S. Pat.
No. 7,706,869 (Cao, et al.), and U.S. Pat. No. 8,428,697 (Zhang, et
al.), all of which are incorporated herein by reference in their
entirety.
[0057] A morphology analysis is performed by tachyarrhythmia
detector 94 using the stored templates to determine whether
morphology matching criteria is met based on a comparison between
an ECG signal received by sensing module 86 during an unknown heart
rhythm and a template generated by cardiac signal analyzer 90
during a known sinus rhythm and stored in memory 82. Numerous
criteria may be used to determine the similarity or correlation
between an ECG signal during an unknown rhythm and a template
obtained during sinus rhythm. In one example, determining whether
morphology matching criteria are met includes determining a
morphology matching score or other metric of morphology similarity.
An example of a morphology feature is a waveform area and a
corresponding example of a morphology match metric may be a
waveform area difference between the ECG signals received from the
selected sensing vectors during an unknown cardiac rhythm and
waveform areas stored for the selected sensing vectors. A
normalized area waveform difference may be determined as generally
disclosed in U.S. patent application Ser. No. 13/826,097, filed
Mar. 14, 2013, (Zhang et al.), hereby incorporated herein by
reference in its entirety. The morphology matching criteria may
require the waveform area difference be within a predetermined
percentage difference.
[0058] A wavelet transform method as generally disclosed in U.S.
Pat. No. 6,393,316 (Gillberg et al.) is another example of a
morphology matching method that may be implemented in the VT/SVT
detection and discrimination techniques disclosed herein. Other
morphology matching methods may be implemented by tachyarrhythmia
detector 94 which compare the wave shape, amplitudes, slopes,
inflection time points, number of peaks, or other features of the
ECG signal, particularly of the R-wave or QRS portion of the ECG
signal. As described herein, tachyarrhythmia detector 94 analyzes
posture-dependent ECG templates for identifying posture-independent
features of the templates. SVT discrimination features are selected
from the posture-independent features for use by tachyarrhythmia
detector 94 for discriminating VT from SVT.
[0059] The ECG morphology received across selected sensing vectors
may vary with changes in patient posture. Comparison of the ECG
morphology during an unknown fast rhythm to a morphology template
obtained during sinus rhythm could result in a low morphology
matching score due to a change in the ECG morphology caused by a
change in patient posture. A fast rhythm that is sinus tachycardia
could potentially be falsely detected as a shockable VT, leading to
unnecessary shock therapy.
[0060] By obtaining multiple morphology templates generated for
each available sensing vector for different patient postures, and
identifying posture-independent features of those templates, those
posture-independent features can be stored in memory 82 and
compared to ECG signal features during an unknown rhythm in
response to VT detection made by cardiac signal analyzer 90 based
on cardiac intervals or other detection criteria. As described
below, the digitized ECG signals received from sensing module 86
using selected sensing vectors during an unknown rhythm are
compared to stored posture-independent template features without
requiring the use of a posture sensor to determine the actual
posture of the patient during the unknown rhythm. In other
embodiments, sensors 96 may include a multi-dimensional
accelerometer for detecting changes in patient posture for use in
initially generating templates for different patient postures, from
which the posture-independent features are extracted. A multi-axis
accelerometer that may be used for detecting patient posture is
generally disclosed in U.S. Pat. No. 5,593,431 (Sheldon), hereby
incorporated herein by reference in its entirety.
[0061] Telemetry module 88 includes a transceiver and antenna for
communicating with external device 40 (shown in FIG. 1) using RF
communication. Under the control of control module 80, telemetry
module 88 may receive downlink telemetry from and send uplink
telemetry to external device 40. ECG episode data related to the
detection of VT or VF and the delivery of a cardioversion or
defibrillation shock may be stored in memory 82. Stored episode
data is transmitted by telemetry module 88 to an external device 40
upon receipt of an interrogation command. Clinician review of
episode data facilitates diagnosis and prognosis of the patient's
cardiac state and therapy management decisions, including selecting
programmable VT/VF detection and therapy delivery control
parameters.
[0062] FIG. 4 is a flow chart 200 of a method performed by ICD 14
for generating morphology templates and extracting
posture-independent discrimination features for detecting and
classifying VT and SVT. At block 202, a targeted patient posture is
detected. An ECG morphology template is stored for multiple patient
postures during a stable heart rhythm. In one example, an ECG
template is generated for each of at least four patient postures
including sitting (or standing but generally upright), supine,
right-side lying, and left-side lying. Other postures may be used
such as forward bending, reclined sitting, prone, etc. Any desired
number and combination of postures may be used. The patient may be
instructed to assume the first of the desired postures, either
automatically by the external device display 54 (shown in FIG. 1)
or by a clinician. A notification may be transmitted to the ICD 14
by user interaction with external device 40 to indicate that the
patient has assumed one of the desired postures for generating a
template. The ICD 14 detects that the patient is in a targeted
posture for template generation in response to receiving the
transmitted notification at block 202.
[0063] Alternatively, the ICD 14 may automatically detect a
targeted patient posture using a posture sensor included in sensors
96 (FIG. 3). A posture sensor signal may be used by the ICD control
module 80 to detect a change from a patient posture to a new
posture. The control module 80 may determine if a template has been
generated and stored in memory 82 for the new posture. If not, the
control module 80 detects the new posture as a targeted posture at
block 202 and initiates template generation by cardiac signal
analyzer 90.
[0064] Prior to generating a template in response to detecting the
targeted patient posture, the ICD 14 may first verify that the
heart rhythm is stable at block 204 using one or more of the
available sensing vectors. A stable heart rhythm may be a sinus
rhythm or other supraventricular rhythm that is verified to have a
stable heart rate over a required number of cardiac cycles and/or a
stable ECG morphology over a required number of cardiac cycles. A
stable rhythm may be normal sinus rhythm, sinus tachycardia, or an
atrial paced rhythm when atrial pacing is available. In some
examples, templates for each targeted posture may be generated at
more than one sinus heart rate since changes in sinus heart rate
can sometimes alter ECG morphology.
[0065] A morphology template may be generated at block 206 for each
available sensing vector while the patient remains in the targeted
posture. For example, the first posture may be a sitting position.
The ICD 14 may generate a morphology template for a sensing vector
between electrodes 28 and 30, a sensing vector between electrode 28
and the housing electrode 15, and a sensing vector between
electrode 30 and the housing electrode 15 while the patient remains
in the sitting position. The morphology template is stored for each
of the three sensing vectors for the first posture. The ICD 14 may
send a notification back to the external device 40 indicating that
template generation is complete for a given posture so that the
process of generating templates can proceed to the next
posture.
[0066] The user may have the opportunity to reject a generated
template if patient movement or other potential source of ECG noise
artifact occurred during the template generation. In some examples,
the ICD 14 may transmit generated templates to the programmer for
display and acceptance by a clinician.
[0067] The patient may then be asked to assume a second posture,
e.g., a supine position. The user may interact with external device
40 to transmit a notification that causes ICD 14 to detect the next
patient posture based on the notification signal and begin ECG
template generation for the second posture. The process of
detecting that the patient has assumed a patient posture, based on
a notification signal from the programmer, verifying a stable heart
rhythm and generating a morphology template for each available
sensing vector is repeated for a desired number of patient postures
until templates for all postures have been obtained for each
sensing vector. As indicated above, the ICD may detect different
patient postures automatically and generate templates as new
postures are detected until a complete set of templates for each of
a desired number of postures for each available ECG sensing vector
is generated.
[0068] The methods used to generate a template at block 206 may
vary between examples. In one example, each template may represent
a series of cardiac cycles that have been aligned over a template
window and averaged to obtain an averaged cardiac cycle waveform
that is stored as the template. A set of morphology templates is
initially generated and stored for each available sensing vector
for a desired number of different patient postures, for example at
least two different postures such as sitting and lying. In one
example, templates are generated for at least four different
postures, e.g., any of sitting, standing, supine, prone, right-side
lying, left-side lying, forward bending and reclined among
others.
[0069] The actual patient posture is not necessarily stored with
each morphology template and may even be unknown to ICD 14. The
generated templates may be stored in ICD memory 82 with labels or
numbering that corresponds to like postures across different
sensing vectors. This labeling or numbering may be non-descriptive
or non-identifying of what the actual patient posture was during
generation of the templates. In other examples, the labeling or
numbering may be descriptive or associated with the actual patient
posture, e.g., based on a notification signal received from the
external device 40 or based upon a posture sensor.
[0070] When a posture sensor is used for detecting a targeted
patient posture for template generation, the actual patient
posture, e.g., sitting, supine, prone, or side-lying, may or may
not be determined. Detection of a change in posture may be adequate
for triggering template generation. The generated templates may be
labeled as Posture 1, Posture 2, Posture 3, etc. for each sensing
vector such that templates generated for a common patient posture
can be identified without necessarily knowing what the actual
patient posture was.
[0071] Once a template is stored for each of a desired number of
patient postures for each available sensing vector as determined at
block 208, the templates generated for different postures for a
given vector are compared to each other at blocks 210 and 212. The
set of generated templates for each sensing vector represents the
posture-dependency of the ECG morphology for a given sensing
vector. This posture dependency may vary between sensing vectors
and between patients. In some cases posture dependency may be high
and in other cases posture dependency may be low or non-existent.
The posture dependency of a given ECG sensing vector will be
determined through the extraction and comparison of template
features.
[0072] At block 210, various features of the templates are
determined and compared to identify template morphology features
that are substantially equal or the same between the
posture-dependent templates for a given sensing vector. A set of
template features is extracted from each template stored for each
posture for each sensing vector. The set of features may include,
without limitation, waveform area, Q-wave amplitude, Q-wave signal
width, Q-wave slope, R-wave amplitude, R-wave signal width, R-wave
slope, T-wave amplitude, T-wave slope, T-wave signal width, R-wave
to Q-wave amplitude ratio, R-wave to T-wave amplitude ratio, R-T
time interval, R-wave polarity, frequency content, number of peaks,
time of maximum peak amplitude, time between maximum and minimum
peaks, time of maximum positive slope, time of maximum negative
slope, amplitude and/or polarity of peaks relative to a largest
amplitude peak, timing of the centroid of the QRS complex, temporal
pattern of a series of amplitude threshold crossings, temporal
pattern of a series of slope threshold crossings, template wavelet
coefficients generated using a wavelet transform, etc.
[0073] At block 212, analogous template features are compared
across posture-dependent templates for a given sensing vector.
Template features that are substantially equal between the
posture-dependent templates are stored for a given sensing vector
and referred to herein as "posture-independent features." These
posture-independent features are extracted from the total set of
template features at block 212 through a comparative analysis. For
example an initial set of ten different template features may be
determined from each posture-dependent template. Each of those ten
template features are compared to the analogous template features
determined from each of the other posture-dependent templates
stored for the same sensing vector.
[0074] If a given template feature does not vary by more than a
posture-independent threshold across templates for a given ECG
sensing vector, that feature is identified as a posture-independent
feature for that sensing vector. For example, if a given template
feature does not vary by more than 10% or another predefined
threshold for determining posture-independence between template
features for the same sensing vector, that template feature is
extracted as a posture-independent feature for that sensing vector
at block 212. As another example, a feature extracted from multiple
cardiac cycles during the same posture may be compared between
cardiac cycles. The range or percentage variation of the feature
between cardiac cycles for the same posture is determined as an
intra-posture range or intra-posture percentage variation. An
inter-posture range or inter-posture percentage variation of the
given feature is also determined between posture-dependent
templates. If the intra-posture range or percentage variation of
the feature is approximately equal to the inter-posture range or
percentage variation, the feature is posture-independent. To
illustrate, a given feature may vary by approximately 5% between
cardiac cycles during the same posture. The same feature may vary
by approximately 5% between postures. Since the feature has the
same inter-posture variability as the intra-posture variability,
the feature is identified as a posture-independent feature.
[0075] The determination of whether a feature from one template is
substantially equal to a feature from another template may include
determining the respective features, determining a difference or
ratio of the features, and comparing the difference or ratio of the
features to a posture-independent threshold. Template sample point
amplitudes may be normalized in some embodiments, e.g., by a
maximum amplitude within a given template and features may be
determined from normalized templates. A posture-independent
threshold may be defined as a percentage, difference, range or
other value based on the type of morphology feature being
determined and compared.
[0076] At block 214, the posture-independent features extracted for
each available sensing vector are stored. It is recognized that in
some cases, available sensing vectors may have varying posture
dependency. As such, a different set of posture-independent
features may be extracted and stored for each available sensing
vector. A set of posture-independent features for one sensing
vector may have a different number of features and/or different
types of features stored than the set of posture-independent
features stored for another sensing vector.
[0077] In some examples, a minimum number of posture-independent
features may be required for each sensing vector. If a sensing
vector is not found to have at least the minimum number of posture
independent features, that sensing vector may be excluded from the
available sensing vectors that can be selected for morphology
analysis during VT/SVT detection and discrimination. The excluded
vector is determined to be highly posture dependent, which may lead
to a false VT detection due to a low morphology match score caused
by posture-induced changes in the ECG signal during a
supraventricular rhythm.
[0078] Once a set of posture-independent features is stored for
each available sensing vector, the stored feature sets are
available for use in a VT/SVT detection and discrimination
algorithm at block 216, as described below in conjunction with FIG.
5. The stored posture-independent feature sets are retrieved from
memory 82 for use in the tachycardia discrimination algorithm
performed by tachyarrhythmia detector 94.
[0079] Some or all of the process shown by flow chart 200 may be
repeated periodically to update the stored posture-independent
feature sets. For example, at block 218, the control module 80 may
determine that it is time to update one or more posture-independent
feature sets. The control module 80 may determine that it is time
to update template feature values according to a scheduled basis,
e.g., once a day, once a week, once a month, or other desired
frequency.
[0080] The control module may additionally or alternatively
determine that it is time to update stored feature values in
response to comparing the feature values to analogous ECG features
during a stable, supraventricular rhythm. For example, once a day
or on another scheduled basis, the stored feature values may be
compared to the ECG signal for a respective sensing vector for one
or more cardiac cycles. Since the features are posture-independent,
the posture of the patient during the comparisons need not be
determined. If the ECG signal during the stable supraventricular
rhythm still matches the stored features for the same sensing
vector within predetermined update criteria, the features are not
updated. The tachyarrhythmia detector 94 continues to use the
presently stored features at block 216. If the ECG signal during
the stable supraventricular rhythm does not match the stored
posture-independent template feature values based on predetermined
update criteria, the control module 80 determines that it is time
for an update.
[0081] If the control module 80 determines that it is time to
update stored template features at block 218, the cardiac signal
analyzer 90 verifies that the cardiac rhythm is a stable,
supraventricular rhythm at block 220. At block 222, new values for
stored template features are re-determined for one or all available
sensing vectors, without determining the patient's posture since
the features have already been identified as being
posture-independent. The re-determined values are stored for each
posture-independent feature for each sensing vector at block 224.
It is recognized that not all available sensing vectors may require
updates at the same time and that updated features may be stored
for some of the available sensing vectors at block 224 but not all
available sensing vectors during each update.
[0082] Periodic updates at block 222 may include obtaining new
values for posture-independent template features stored for a given
sensing vector without re-determining which template features are
posture-independent for that sensing vector. It may be assumed that
the features that are first identified at block 212 as being
posture-independent for a given sensing vector will remain
independent. Only the values of the posture-independent features
need updating.
[0083] In other cases, the feature set may be periodically
re-evaluated for posture-independency. Accordingly, in some
examples, the process shown by FIG. 4 may be repeated beginning at
step 202 for updating the set of posture-independent template
features that is stored for a given sensing vector. Templates may
be generated at block 206 for each sensing vector to be updated for
multiple patient postures as described above. The variation or
range of previously identified posture-independent features may be
re-determined from the newly generated templates at block 210 to
verify that each feature remains posture-independent without
requiring determining and comparing a larger number of template
features. Alternatively, a larger set of posture-independent
features is determined at block 210 a described above, from which a
new set of posture-independent template features is extracted at
block 212. The members of the posture-independent feature set may
change over time in some cases.
[0084] FIG. 5 is a flow chart 300 of a method for discriminating
between VT and SVT according to one example. At block 302, an ECG
signal is received across one or more selected sensing vectors.
Referring to the example of FIG. 1, ECG1 may be an ECG signal
received across the vector between sensing electrodes 28 and 30.
ECG2 may be an ECG signal received across the vector between
electrode 28 and the housing electrode 15, and ECG3 may be an ECG
signal received across electrodes 30 and the housing electrode 15.
ICD 14 may be configured with at least two sensing channels and may
select two out of three available sensing vectors, such as two out
of ECG1, ECG2 and ECG3. In other examples, one or more ECG sensing
vectors may be selected from one or more available sensing
vectors.
[0085] In some examples, VT is initially detected based on heart
rate. R-wave sense signals are produced by the ICD sensing module
in response to R-wave sensing threshold crossings of at least one
or all selected ECG signals. RR intervals are determined by the
cardiac signal analyzer 90 in response to R-wave sense signals. RR
intervals are used at block 304 to detect VT according to rate or
interval-based VT detection criteria. For example, VT may be
detected based on a required number of intervals to detect (NID)
falling into a programmed VT interval range. To illustrate, a VT
detection interval range may include RR intervals less than or
equal to 360 ms and greater than 320 ms. A ventricular fibrillation
detection interval (FDI) range may be defined as RR intervals less
than or equal to 320 ms. The VT NID may be set to 12 consecutive
intervals, 24 consecutive intervals or another required number of
VT detection intervals. If the required number of consecutive RR
intervals are in the VT detection interval range, a preliminary VT
detection may be made.
[0086] In other examples, primary VT detection criteria may include
a prioritized set of inter-related rules pertaining to cardiac
intervals, interval patterns and or morphology; rate onset;
stability; and/or gross morphology detection criteria or any
combination thereof. Various examples of VT detection criteria that
may be used as primary detection criteria at block 304 are
disclosed in the above-incorporated patents, such as U.S. Pat. No.
5,545,186 (Olson, et al.), U.S. Pat. No. 7,031,771 (Brown, et al.),
U.S. Pat. No. 8,160,684 (Ghanem, et al.), and U.S. Pat. No.
8,437,842 (Zhang, et al.).
[0087] If VT detection is made based on RR intervals or other
primary detection criteria, at block 304, a comparative morphology
analysis of the unknown rhythm with posture-independent template
features is performed at blocks 306 through 310 before confirming a
VT rhythm classification and delivering a VT therapy. The
morphology analysis is performed to determine if the morphology of
the received ECG signal(s) during the unknown rhythm matches
posture-independent template features stored for the corresponding
ECG sensing vector(s).
[0088] In order to make this comparison, the cardiac signal
analyzer determines which posture-independent features have been
stored for a given sensing vector. Those features are then
determined from the ECG signal at block 306 during the unknown
rhythm, which has been preliminarily detected as VT based on RR
interval or other primary detection criteria. The features may be
determined from single cardiac cycles over one or more beats for
performing beat-by-beat feature comparisons. Alternatively, one or
more cardiac cycles during the unknown rhythm may be aligned within
a morphology analysis window and ensemble averaged. The ECG
features are then determined from the averaged cardiac cycle at
block 308.
[0089] If more than one ECG signal is being monitored, the
posture-independent features that have been stored for each sensing
vector are determined from each respective ECG signal. The actual
patient posture need not be determined since the features being
determined have been identified as posture-independent
features.
[0090] At block 308, the features determined from the ECG signal(s)
during the unknown rhythm are compared to the stored,
posture-independent template features for each respective sensing
vector. If features have been extracted from single cardiac cycles
of the ECG signal during the unknown rhythm, a beat-by-beat
comparison may be made. In one example, if a feature of at least n
out of m beats, for example 3 out of 5 beats, match the analogous
posture-independent template feature, that feature is determined to
match the template feature. Alternatively, the features extracted
from the ensemble averaged signal during the unknown cardiac rhythm
are compared to the analogous posture-independent template
features. The comparison between individual beat features or an
ensemble averaged cardiac cycle signal to determine a similarity
between the unknown cardiac rhythm and the stored template features
may involve determining a morphology match metric for each feature
as a percentage, sign change, numerical difference, ratio, or other
comparative parameter for each posture-independent feature.
[0091] The morphology match metric of a given feature during the
unknown rhythm may be determined as the difference between the
feature and the template feature expressed as a percentage of the
stored template feature. For example, an R-wave width metric may be
determined as ((1-R-wave width difference)/template R-wave
width)*100, where R-wave width difference is the absolute
difference between the R-wave width of an unknown individual beat
or averaged cardiac cycle and the template R-wave width. If the
R-wave width metric is at least 90%, the R-wave width of the
cardiac signal during the unknown rhythm and the R-wave width
template feature match.
[0092] In another example, a normalized waveform area difference
(NWAD) may be determined as ((1-AD)/TEMPLATE WA)*100 where AD is
the absolute area difference between the normalized ECG signal
waveform during an unknown rhythm and the normalized template
waveform. TEMPLATE WA (waveform area) is the area of the normalized
template waveform. The waveforms may be normalized by a maximum
sample point amplitude of the waveform. If the NWAD is at least 90%
(or other threshold percentage), the WA of the unknown signal
matches the WA of the template.
[0093] Once a morphology match metric for each posture-independent
feature for each ECG sensing vector has been determined, overall
morphology match criteria are applied at block 310 to the
morphology match metrics. In some examples, each ECG vector signal
during the unknown rhythm is first classified as SVT or VT based on
the morphology match metrics determined for each
posture-independent feature for that sensing vector. Each
morphology match metric may be compared to a match threshold to
determine if an individual morphology match metric of an individual
ECG feature matches the posture-independent feature. Actual values
defined as the morphology match thresholds applied to different
posture-independent feature comparisons may vary between
embodiments and will be based on the type of signal feature being
compared. Different morphology match criteria may be applied to
different posture-independent features. For example some features
may be required to match a posture-independent template feature
more closely than other features.
[0094] An ECG vector signal during the unknown rhythm may be
classified as SVT if a required number of the ECG signal features
during the unknown rhythm match the posture-independent template
features for that sensing vector based on a morphology match
criteria for each respective feature. Morphology match criteria
applied to a single vector may require at least one feature be
within a predetermined range or percentage, e.g., 10% or other
predetermined percentage threshold, of the analogous
posture-independent template feature. To illustrate, if one of the
stored posture-independent features is QRS signal width, and the
template QRS signal width is 120 ms, the ECG signal during the
unknown rhythm may be required to be within 10 ms or 10% of the
template QRS signal width.
[0095] If n posture-independent template features have been stored
for a given sensing vector, at least one of the n
posture-independent template features may be required to match the
analogous ECG signal feature during the unknown rhythm based on
matching criteria for the respective features in order to classify
that sensing vector as SVT. In another example, a majority of the
stored posture-independent template features, e.g. two out of three
stored posture-independent template features, may be required to
match analogous ECG signal features within respective matching
criteria in order to classify the sensing vector signal as SVT. In
some cases, all features determined from one sensing vector may be
required to match all analogous posture-independent template
features within respective matching criteria for that sensing
vector in order to classify that sensing vector signal as SVT
during the unknown rhythm. If no ECG signal features, or less than
a threshold number of ECG signal features, match the analogous
posture-independent template features based on matching criteria
defined for each feature or defined for a combination of features,
the sensing vector is classified as VT.
[0096] Once each sensing vector is classified as SVT or VT, an
overall SVT or VT detection is made at block 316 or block 312. In
one example, SVT detection criteria require that at least one
sensing vector yields an SVT classification at block 316.
Morphology match criteria applied at block 310 are also referred to
herein as "SVT detection criteria" since a match would indicate
that the rhythm is supraventricular in origin.
[0097] In other examples, SVT detection criteria applied at block
310 may include different logical combinations of the morphology
matching results determined for features from multiple ECG vectors
without classifying the individual ECG sensing vectors during the
unknown rhythm. For example, if at least one signal feature from
one sensing vector matches a respective posture-independent
template feature, and at least one ECG signal feature from another
sensing vector matches a respective posture-independent template
feature, or if at least two ECG signal features from the same
sensing vector match respective posture-independent template
features, SVT may be detected at block 316. In other words, if the
ECG signal from each sensing vector matches a first threshold
number of template features, e.g., one each, or if the ECG signal
of only sensing vector matches a second, higher threshold number of
template features, e.g., at least two, SVT is detected. In an
example where three posture-independent features are stored for
each of two sensing vectors, this decision step may be stated
logically as: [0098] IF one of ECG1 features 1, 2, or 3 match AND
one of ECG2 features 1, 2 or 3 match, [0099] THEN SVT; [0100] OR
[0101] IF two of ECG1 features 1, 2, and 3 match OR two of ECG2
features 1, 2, and 3 match, [0102] THEN SVT; [0103] ELSE VT.
[0104] It is recognized that numerous SVT detection criteria may be
conceived that are based on different combinations of
posture-independent feature comparisons from one or more ECG
sensing vectors.
[0105] If SVT is detected at block 316, VT therapy is not
delivered. In particular, a shock therapy is withheld as indicated
at block 318 since the SVT is deemed a non-treatable rhythm. ECG
monitoring continues by returning to block 302. If the SVT
detection criteria are not satisfied at block 310, the primary VT
detection made at block 304 is confirmed at block 312. The ICD 14
delivers a therapy to treat the VT at block 314. A
cardioversion/defibrillation shock may be delivered. In IMD systems
that include pacing capabilities, ATP may be delivered prior to
delivering a shock therapy.
[0106] The SVT detection criteria applied at block 310 based on
posture-independent feature comparisons are described as being
secondary VT/SVT detection criteria that are applied only after a
preliminary VT detection has been made based on primary VT
detection criteria, such as RR interval-based criteria. In other
examples, the morphology match criteria applied to comparisons
between an ECG signal during an unknown rhythm with
posture-independent template features may be the primary VT
detection criteria, used with or without other primary and/or
secondary detection criteria.
[0107] FIG. 6 is a multi-dimensional plot 400 of
posture-independent features depicting an SVT classification region
410. Plot 400 depicts an alternative method that may be performed
by cardiac signal analyzer 90 for classifying an ECG sensing vector
as SVT or VT during an unknown cardiac rhythm. In an illustrative
example, multiple features may be extracted from each
posture-dependent template for a given ECG sensing vector, for
example eight, ten or more features of the posture-dependent
template. After comparing the features, a set of
posture-independent features for the sensing vector is identified.
This process corresponds to the flow chart 200 shown in FIG. 4. The
resulting set of posture-independent features may vary in the
number of features identified as being posture-independent. In the
example shown in FIG. 6, a set of three features are identified as
posture independent features for the given ECG sensing vector.
These three features can be visualized in a three-dimensional plot
400, with Feature 1 plotted along an x-axis 402, Feature 2 plotted
along a y-axis 404 and Feature 3 plotted along a z-axis 406.
[0108] The point "X" 408 indicates the location of the template
values of three posture-independent features, Feature 1, Feature 2
and Feature 3, determined as x-, y- and z-coordinates in the
three-dimensional space of plot 400 for a given sensing vector. For
example, Feature 1 may be R-wave width, Feature 2 may be Q-wave
width, and Feature 3 may be the time of maximum positive R-wave
slope. It is recognized that a plot of posture-independent features
for a given ECG sensing vector may be 1-dimensional, 2-dimensional,
3-dimensional or any n-dimensional plot where "n" is the number of
posture-independent features identified for the given ECG sensing
vector.
[0109] The SVT classification region 410 is defined by a morphology
match threshold range 412, 414, and 416 for each respective Feature
1, Feature 2, and Feature 3. The morphology match threshold ranges
may represent a range of values for a given feature that is within
+5%, .+-.10% or other acceptable range of the template feature
value. Six individual cardiac cycles during an unknown rhythm are
represented by points 1-6 420 (circle symbols). The cardiac cycles
1 through 6 during the unknown rhythm have been analyzed
beat-by-beat to determine the values of Feature 1, Feature 2, and
Feature 3 for each cycle. The cardiac cycle feature values are
represented by each of the plotted cardiac cycle points 1-6 420. In
other words, the features of each cardiac cycle are represented by
the x-, y- and z-coordinates of points 1-6 420 in the three
dimensional space.
[0110] Cardiac cycles 2, 4, 5 and 6 fall within the SVT
classification region 410 and represent cardiac cycles having
morphology features matching the three analogous
posture-independent template features based on morphology match
threshold ranges 412, 414, and 416. Cardiac cycles 2, 4, 5 and 6
are classified as SVT cycles. Cardiac cycles 1 and 3 fall outside
the SVT classification region 410 and represent cardiac cycles that
do not match the posture-independent template features. Cardiac
cycles 1 and 3 are classified as VT cycles. In one example, if n of
m cycles are classified as SVT points because they fall within the
SVT classification region 410, e.g., if four out of six cardiac
cycle points fall within the SVT classification region 410 as
shown, the ECG signal for the sensing vector being analyzed is
classified as SVT. If less than n of m cardiac cycles fall within
the SVT classification region 410, the ECG sensing vector is
classified as VT. In other examples, an ECG sensing vector is
classified as VT if at least a threshold number of consecutive
cardiac cycles are classified as VT, i.e., all cardiac cycle points
fall outside SVT classification region 410. In some instances, 12,
24 or another number of consecutive cardiac cycle points may be
required to fall outside the SVT classification region 410 in order
to classify the ECG sensing vector signal during the unknown rhythm
as a VT signal.
[0111] If only one ECG sensing vector is being used, the unknown
rhythm is detected as SVT or VT based on the SVT or VT
classification of that sensing vector. If more than one ECG sensing
vector is being used, SVT is detected if at least one sensing
vector is classified as SVT during the unknown rhythm.
[0112] In other examples, an ensemble averaged cardiac cycle during
the unknown rhythm is compared to the posture-independent template
features. In this case, a single point, e.g., Point 1 may be
determined as having x-, y-, z-coordinates set equal to the values
determined from the averaged cardiac cycle for each respective
Feature 1, Feature 2 and Feature 3. If Point 1 falls outside the
SVT classification region 410 as shown, the ECG sensing vector
signal is classified as VT during the unknown rhythm. If a single
point representing the posture-independent features of an averaged
cardiac cycle falls within the SVT classification region 410, the
ECG sensing vector signal is classified as SVT during the unknown
rhythm.
[0113] The cubic shape of the SVT classification region 410
depicted in FIG. 6 is a case where the acceptable values of the
posture-independent features are independent of each other. It is
also recognized that the shape of the SVT classification region 410
of FIG. 6 can take a form where the acceptable values of the
features are interdependent resulting in a sphere, ellipsoid, or
other shape, and is not constrained to 3 dimensions based on three
posture-independent features.
[0114] In some cases, a morphology match threshold applied to a set
of features determined from an ECG signal during an unknown rhythm
may be defined as a maximum distance from the template point 408 in
the n-dimensional space of plot 400. The distance 422 in the
n-dimensional space between Point 1 for the unknown cardiac signal
and the template point 408 may be determined based on mathematical
relationships. The distance 422 is compared to a morphology match
distance threshold. If the distance 422 is greater than a
morphology match threshold, Point 1 is classified as a VT point. If
the distance 422 is less than the morphology match threshold, the
point is classified as an SVT point. If the point represents an
ensemble average of multiple cardiac cycles of the unknown rhythm,
the ECG sensing vector signal is classified according to the
classification of the point. Alternatively, if multiple points are
classified in a beat-by-beat analysis, the ECG sensing vector
signal is classified based on a required number of points being
within (or more than) a morphology match distance threshold. For
example, if a threshold number of consecutively determined points
are more than the threshold distance from the template feature
point 408, the sensing vector is classified as VT. A final VT or
SVT detection is based on the classifications of one or more ECG
sensing vector signals during the unknown rhythm.
[0115] FIG. 7 is a flow chart 500 of a method for performing VT
detection according to another example. At block 502, a set of
posture-independent template features is generated for each
available sensing vector, e.g., as described in conjunction with
FIG. 4. In some patients, ECG signals may be posture-independent
and in other patients, changes in posture alter the ECG signals. In
patients presenting posture-independency, the set of template
features determined for one posture matches the set of template
features for all postures for a given sensing vector. If all ECG
sensing vectors are posture independent, as determined at block
504, the cardiac signal analyzer 90 may perform VT detection
without performing a comparison of ECG signal features to
posture-independent template features, as indicated at block 506.
For example, any interval and/or morphology based detection
criteria may be used without determining posture-independent
features of the ECG signal or comparing those features to stored
posture-independent template features.
[0116] If all vectors are not posture independent (block 504), the
posture-independent features sets are stored for each of the
sensing vectors at block 508. The VT detection algorithm performed
by ICD 14 will include comparisons to posture-independent template
features (for at least some ECG sensing vectors).
[0117] At block 510, ECG sensing vectors are selected for VT
detection. One or more vectors may be selected. Vector selection
may be based at least in part on the posture dependency of each
available vector. In some cases, a single vector may be highly
posture dependent such that all features or a majority of features
are posture dependent (none or a small minority of the template
features are stored as posture-independent features). Other vectors
may be relatively less posture dependent with a relatively larger
number of posture-independent features stored. Vector selection at
block 510 may therefore include selecting one or more vectors that
present the highest posture independency based on the number of
posture-independent features stored. Vectors having a higher number
of posture-independent features may be selected before vectors
having a lower number of posture-independent features stored. All
or a subset of the posture-independent features stored may actually
be used for comparison to ECG signal features during an unknown
rhythm. Posture-independency may be one criterion used for ECG
sensing vector selection among other selection criteria, such as
signal-to-noise ratio or other signal quality parameter
requirements.
[0118] At block 512, VT is detected based on primary detection
criteria, e.g., based on RR intervals, RR interval stability, rate
onset, and/or gross morphology. In some cases, the ECG signal(s)
used for primary VT detection at block 512 may be the same or
different than the ECG signal(s) selected at block 510 for
posture-independent template feature comparisons.
[0119] In response to a preliminary VT detection, ECG signal
features are determined from each sensing vector selected at block
510 that are analogous to the stored posture-independent template
features for the respective sensing vector. As indicated above, all
or a subset of stored posture-independent template features may be
used. Based on a comparative analysis of the ECG signal features
and the corresponding posture-independent template features, e.g.,
as described in conjunction with FIG. 5 or 6, each selected ECG
signal vector is classified as an SVT or VT rhythm at block
514.
[0120] If at least one ECG sensing vector is classified as SVT, as
determined at block 516, the unknown rhythm is detected as SVT at
block 518. In another example, SVT detection criteria may require
that all selected ECG sensing vectors are classified as SVT. If
none of the selected ECG sensing vectors are classified as SVT, the
primary VT detection at block 512 is confirmed at block 520.
[0121] Thus, a method and apparatus for detecting and
discriminating VT and SVT have been presented in the foregoing
description with reference to specific embodiments. In other
examples, various methods described herein may include steps
performed in a different order or combination than the illustrative
examples shown and described herein. It is appreciated that various
modifications to the referenced embodiments may be made without
departing from the scope of the disclosure and the following
claims.
* * * * *