U.S. patent application number 14/853640 was filed with the patent office on 2016-03-10 for determining onsets and offsets of cardiac depolarization and repolarization waves.
The applicant listed for this patent is Medtronic, Inc.. Invention is credited to Subham Ghosh.
Application Number | 20160067498 14/853640 |
Document ID | / |
Family ID | 51355634 |
Filed Date | 2016-03-10 |
United States Patent
Application |
20160067498 |
Kind Code |
A1 |
Ghosh; Subham |
March 10, 2016 |
DETERMINING ONSETS AND OFFSETS OF CARDIAC DEPOLARIZATION AND
REPOLARIZATION WAVES
Abstract
An exemplary computer-implemented method is disclosed for
detection of onset of depolarization on far-field electrograms
(EGMs) or electrocardiogram (ECG)-or ECG-like signals. The method
includes determining a baseline rhythm using a plurality of
body-surface electrodes. The baseline rhythm includes an atrial
marker and a ventricular marker. A pre-specified window is defined
as being between the atrial marker and the ventricular marker. A
low pass filter is applied to a signal within the window. A
rectified slope of the signal within the window is determined. A
determination is made as to whether a time point (t1) is present
such that the rectified slope exceeds 10% of a maximum value of the
rectified slope. A point of onset of a depolarization complex in
the signal is determined. The point of onset occurs at a largest
curvature in the signal within the window.
Inventors: |
Ghosh; Subham; (Blaine,
MN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Medtronic, Inc. |
Minneapolis |
MN |
US |
|
|
Family ID: |
51355634 |
Appl. No.: |
14/853640 |
Filed: |
September 14, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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13952076 |
Jul 26, 2013 |
9132274 |
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14853640 |
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Current U.S.
Class: |
607/9 |
Current CPC
Class: |
A61N 1/36507 20130101;
A61B 5/0036 20180801; A61N 1/3684 20130101; A61B 2562/043 20130101;
A61B 5/04085 20130101; A61B 5/4836 20130101; A61B 5/1107 20130101;
A61B 5/0402 20130101; A61N 1/3627 20130101; A61B 5/04017 20130101;
A61B 5/0452 20130101; A61N 1/36842 20170801; A61B 2562/046
20130101 |
International
Class: |
A61N 1/365 20060101
A61N001/365; A61B 5/0408 20060101 A61B005/0408; A61B 5/0452
20060101 A61B005/0452; A61N 1/362 20060101 A61N001/362 |
Claims
1. A method of cardiac pacing comprising: a) determining a baseline
rhythm using a plurality of body-surface electrodes, the baseline
rhythm includes an atrial marker and a ventricular marker (Vs); b)
defining a pre-specified window between the atrial marker and the
ventricular marker; c) applying a low pass filter to a signal
within the window; d) determining a rectified slope of the signal;
e) determining a time point (t1) in which the rectified slope
exceeds 10% of a maximum value of the rectified slope; f)
determining a point of onset of a depolarization complex in the
signal; g) determine an electromechanical delay for each of a
plurality of candidate cardiac pacing lead sites using the
determined point of onset of the depolarization complex; and h)
select an implant site for a pacing lead for delivering cardiac
pacing based upon the determined electromechanical delays.
2. The method of claim 1 wherein automated determination of the
point of onset of the depolarization complex is performed without
detection of a threshold.
3. The method of claim 1 wherein the largest curvature in the
signal is determined from a curvature of the signal defined as
r=|y''|/(1+|y'|.sup.2).sup.(3/2) in which y'' and y' are the double
and single derivatives of y=f(t), respectively.
4. The method of claim 1 wherein a simplified version of a
curvature equation, r.apprxeq.|y''|/(1+|y'|2), may be used to
compute an index that tracks the curvature of the signal,
eliminating computation of square roots.
5. The method of claim 2 wherein determining the point of onset of
the depolarization complex comprises searching for the largest
curvature of the signal or an index tracking a curvature of the
signal at a sharp deflection in the curvature of the signal, the
sharp deflection being indicative of the onset of the
depolarization complex.
6. The method of claim 1 further comprising: searching for the
largest curvature within the pre-specified window and ending on a
maximum peak or a minimum valley.
7. The method of claim 1 further comprising: removing
high-frequency artifacts in the signal through the low pass
filter.
8. The method of claim 1 further comprising: receiving an ECG
signal by a cardiac resynchronization therapy (CRT) device, wherein
determining the point of onset of the depolarization complex
comprises determining a point of onset of a QRS complex in the ECG
signal received by the CRT device.
9. The method of claim 18 wherein receiving the ECG signal by the
CRT device includes receiving one of a leadless ECG signal and a
far-field ECG signal.
10. The method of claim 8 further comprising: automating
measurements of cardiac electrical activation times with respect to
the determined point of onset of the QRS complex.
11. A system of cardiac pacing comprising: a) processing means for
determining a baseline rhythm using a plurality of body-surface
electrodes, the baseline rhythm includes an atrial marker and a
ventricular marker (Vs); b) processing means for defining a
pre-specified window between the atrial marker and the ventricular
marker; c) processing means for applying a low pass filter to a
signal within the window; d) processing means for determining a
rectified slope of the signal; e) processing means for determining
a time point (t1) in which the rectified slope exceeds 10% of a
maximum value of the rectified slope; f) processing means for
determining a point of onset of a depolarization complex in the
signal, wherein the point of onset occurs at a largest curvature in
the signal; g) processing means for determining an
electromechanical delay for each of a plurality of candidate
cardiac pacing lead sites using the determined point of onset of
the depolarization complex; and h) processing means for selecting
an implant site for a pacing lead for delivering cardiac pacing
based upon the determined electromechanical delays.
12. The system of claim 11 wherein automated determination of the
point of onset of the depolarization is performed without detection
of a threshold.
13. The system of claim 11 wherein the largest curvature in the
signal is determined from a curvature in the signal defined as
r=|y''|/(1+|y'|.sup.2).sup.(3/2) in which y'' and y' are the double
and single derivatives of y=f(t), respectively.
14. The system of claim 11 wherein a simplified version of a
curvature equation r.apprxeq.|y''|/(1+|y'|2), may be used to
compute an index that tracks the curvature of the signal thereby
eliminating computation of square roots.
15. The system of claim 12 wherein determining the point of onset
of the depolarization complex comprises searching for the largest
curvature in the signal or an index tracking a curvature of the
signal at a sharp deflection in the curvature of the signal, the
sharp deflection being indicative of the onset of the
depolarization complex.
16. The system of claim 11 further comprising: processing means for
searching for the largest curvature within the pre-specified window
and ending on a maximum peak or a minimum valley.
17. The system of claim 11 further comprising: removing
high-frequency artifacts in the signal through the low pass
filter.
18. The system of claim 11 further comprising: receiving means for
receiving an ECG signal by a cardiac resynchronization therapy
(CRT) device wherein determining the point of onset of the
depolarization complex comprises determining a point of onset of a
QRS complex in the ECG signal received by the CRT device.
19. The system of claim 18 wherein the receiving means for
receiving the ECG signal by the CRT device includes means for
receiving one of a leadless ECG signal and a far-field ECG
signal.
20. The system of claim 18 further comprising: processing means for
automating measurements of cardiac electrical activation times with
respect to the determined point of onset of the QRS complex.
21-27. (canceled)
Description
RELATED APPLICATION
[0001] This application is a continuation of U.S. patent
application Ser. No. 13/952,076, filed Jul. 26, 2013 entitled
"DETERINING ONSETS AND OFFSETS OF CARDIAC DEPOLARIZATION AND
REPOLARIZATION WAVES", herein incorporated by reference in its
entirety.
TECHNICAL FIELD
[0002] The invention relates to medical devices, and more
particular, to medical devices for sensing, detection, and analysis
of cardiac electrograms and electrocardiograms.
BACKGROUND
[0003] Implantable medical devices (IMDs), such as implantable
pacemakers, cardioverters, defibrillators, or
pacemaker-cardioverter-defibrillators, provide therapeutic
electrical stimulation to the heart. IMDs may provide pacing to
address bradycardia, or pacing or shocks in order to terminate
tachyarrhythmia, such as tachycardia or fibrillation. In some
cases, the medical device may sense intrinsic depolarizations of
the heart, detect arrhythmia based on the intrinsic depolarizations
(or absence thereof), and control delivery of electrical
stimulation to the heart if arrhythmia is detected based on the
intrinsic depolarizations.
[0004] IMDs may also provide cardiac resynchronization therapy
(CRT), which is a form of pacing. CRT involves the delivery of
pacing to the left ventricle, or both the left and right
ventricles. The timing and location of the delivery of pacing
pulses to the ventricle(s) may be selected to improve the
coordination and efficiency of ventricular contraction.
[0005] IMDs sense signals and deliver therapeutic stimulation via
electrodes. Implantable pacemakers, cardioverters, defibrillators,
or pacemaker-cardioverter-defibrillators are typically coupled to
one or more subcutaneous electrodes or intracardiac leads that
carry electrodes for cardiac sensing and delivery of therapeutic
stimulation. The signals sensed via the electrodes may be referred
to as a cardiac electrogram (EGM) and may include the
depolarizations, repolarizations, and other intrinsic electrical
activity of the heart.
[0006] Systems for implanting medical devices may include
workstations or other equipment in addition to the medical device
itself. In some cases, these other pieces of equipment assist the
physician or other technician with placing the intracardiac leads
at particular locations on the heart. In some cases, the equipment
provides information to the physician about the electrical activity
of the heart and the location of the intracardiac lead. The
equipment may perform similar functions as the medical device,
including delivering electrical stimulation to the heart and
sensing the depolarizations of the heart. In some cases, the
equipment may include equipment for obtaining an electrocardiogram
(ECG) via electrodes on the surface of the patient. In addition,
the patient may have a plurality of electrodes on an ECG belt or
vest that surrounds the torso of the patient. After the vest has
been secured to the torso, a physician can perform a series of
tests to evaluate a patient's cardiac response. The evaluation
process can include detection of a baseline rhythm in which no
electrical stimuli is delivered to cardiac tissue and another
rhythm after electrical stimuli is delivered to the cardiac tissue.
During the evaluation process, a physician typically needs to
review the onset of cardiac depolarization waves in the rhythms.
Reliable detection of depolarization waves assists the physician in
setting parameters for optimal delivery of CRT. However, most
algorithms require threshold detection of the depolarization signal
or its derivative. Threshold detection may not reliably and
consistently detect onset of cardiac depolarization for all
patients and there may be inherent non-physiologic (e.g. noise)
variations in thresholded parameters like slopes, amplitudes etc.
from one cardiac cycle to another. It is therefore desirable to
develop methods and systems of determining onset of cardiac
depolarization waves in signals without the use of threshold
detection.
BRIEF DESCRIPTION OF DRAWINGS
[0007] FIG. 1 is a block diagram illustrating and example system
that may determine the onsets and offsets of various heart
repolarization and depolarization waves.
[0008] FIG. 2 is a block diagram illustrating an example
configuration of a wave detection module.
[0009] FIG. 3 is a graph illustrating an example cardiac
electrogram.
[0010] FIG. 4 is a graph illustrating an example cardiac
electrogram including R-wave marker information.
[0011] FIG. 5 is a graph illustrating an example cardiac
electrogram including R-wave marker information and example windows
around each marker.
[0012] FIG. 6 is a graph illustrating an example cardiac
electrogram including example determined wave onset points.
[0013] FIG. 7 is a graph illustrating both a cardiac contraction
curve and a surface ECG curve with indicators marking the
determined onset of depolarization of the heart and the detected
timing of local heart mechanical contraction.
[0014] FIG. 8 is a graph illustrating both a cardiac contraction
curve at a potential intracardiac lead implant site and a local EGM
curve from the same potential implant site with indicators marking
the determined onset of local depolarization of the heart and the
detected timing of local heart mechanical contraction.
[0015] FIG. 9 is a flow diagram illustrating an example technique
for selecting intracardiac lead implant sites.
[0016] FIG. 10 is a flow diagram illustrating an example technique
for selecting intracardiac lead implant site.
[0017] FIG. 11A is a conceptual diagram illustrating an example
system that determines the onset and offsets of heart
depolarization and repolarization waves.
[0018] FIGS. 11B-11C are conceptual diagrams illustrating exemplary
systems for measuring torso-surface potentials. FIG. 12 is a
conceptual diagram illustrating the implantable medical device
(IMD) and leads of the system shown in FIG. 11A in greater
detail.
[0019] FIG. 13 is a block diagram of an example implantable medical
device that may determine the onset and offset of heart
depolarization and repolarization waves.
[0020] FIG. 14 illustrates an example of the time-delay between the
delivery of pacing and the onset of depolarization.
[0021] FIG. 15 is a flow diagram illustrating an example technique
for detection of onset of heart depolarization waves.
[0022] FIG. 16A is graphically depicts a cardiac ECG signal.
[0023] FIG. 16B graphically depicts a curvature relative to the
cardiac ECG signal shown in FIG. 16A.
DETAILED DESCRIPTION
[0024] The techniques and methods described in this disclosure
allow a system to determine the onsets and offsets of heart
depolarization waves and/or repolarization waves during the process
of implanting the implantable medical device (IMD) or post-implant
(e.g. periodic medical check-ups after the device has been
implanted).
[0025] A computer-implemented method, embodied in FIG. 15, is
directed to detection of onset of depolarization on far-field
electrograms (EGMs), electrocardiograms (ECG)-or ECG-like signals.
An ECG-like signal can be for example, a far-field intracardiac
electrogram obtained from a device or invasively measured using a
mapping wire inside the heart or it can be a leadless ECG generated
by an implantable medical device. The method includes determining a
baseline rhythm using a plurality of body-surface electrodes. The
baseline rhythm includes an atrial marker and a ventricular marker.
The atrial marker is associated with an atrial event while a
ventricular marker is associated with a ventricular event. Each
marker can be displayed to a user on a graphical user interface of
a computer such as a programmer. A pre-specified time-window is
defined as being between the timing of the atrial marker and timing
of the ventricular marker. A low pass filter is then applied to a
signal (usually a ECG signal or surrogate of an ECG signal like a
far-field EGM, leadless device ECG, etc.) within the window. A
rectified slope of the signal within the window is determined. A
determination is then made as to whether a time point (t1) is
present such that the rectified slope exceeds 10% of a maximum
value of the rectified slope. A point of onset of a depolarization
complex in the signal is then determined. The point of onset occurs
at a largest curvature in the signal within the window from the
voltage of the signal of the ventricular marker (Vs)-100 ms to t1,
as shown in FIG. 16A. Vs refers to the timing of a ventricular
event, for example ventricular sensing, as detected by the sensing
circuits within the IMD. A curvature is defined as
r=|y''|/(1+|y'|.sup.2).sup.(3/2) in which y'' and y' are the double
and single derivatives of a time varying signal y respectively
where the time-varying signal is the signal acquired from surface
electrodes and/or electrodes associated with an implanted medical
device. The first and second derivatives of y can be determined
using a variety of known methods. For example, the first
derivative, y', can be determined based on finite difference
methods (e.g. difference between successive time samples). The
second derivative, y'' can be similarly calculated but instead of
using y, different points along y' curve are used.
[0026] In some examples, the diagnostic metrics may be used to
optimize or otherwise guide the configuration of therapy, such as
cardiac resynchronization therapy (CRT). For CRT, lead placement,
pacing electrode configuration, or various atrio-ventricular or
interventricular intervals may be configured based on metrics that
are determined based on the identified onsets and/or offsets. In
some examples, electromechanical delay may be used to configure CRT
and, particularly, to select a lead placement, e.g.
left-ventricular lead placement, during implantation of a CRT
system.
[0027] In general, a heart produces a repetitive electrical signal
which causes the heart to mechanically contract, thereby pumping
blood throughout the body. Generally, the signal may be detected
and displayed as a cardiac electrogram signal. Although the exact
representation may differ depending on the placement of leads on or
within the body to detect the heart signal, among other factors, a
common cardiac electrogram includes several recognizable features.
The initial deflections of the signal represent the P-wave and the
QRS complex. The P-wave represents the depolarization of the atria
and the QRS complex represents the depolarization of the
ventricles. The Q-wave of the QRS complex is the initial downward
deflection of the signal during the complex. Following the Q-wave
is the R-wave, which is an upward deflection of the signal.
Finally, the S-wave is another downward deflection. The next
portion of the signal represents repolarization of the atria and
ventricles. More specifically, what is generally called the T-wave
represents the repolarization of the ventricles. There is no
specific wave or feature of the signal that represents the
repolarization of the atria because the generated signal is small
in comparison to the T-wave. Together, the P-wave, the Q, R, and S
waves, and the T-wave represent the depolarization and
repolarization waves of a heart electrical signal.
[0028] The described techniques may enhance the accuracy of
determining the onsets and offsets of the various waves which
comprise the repeated cardiac electrogram signal. In particular,
knowing more accurately the timing of the onsets and offsets of the
waves allows for a more accurate determination of the
electrical-electrical delays and the electromechanical delays. For
example, the point of onset of ventricular depolarization on
surface ECG forms a fiducial element (also simply referred to as
"fiducial" or marker) with respect to which local electrical
activation or depolarization times and may be measured at different
sites in the ventricle. During implant of a heart lead for cardiac
resynchronization therapy, the time-interval between this onset
point and the time of local activation or depolarization at a
candidate implant site within the ventricle may be evaluated and if
it exceeds a certain threshold (e.g. 90 ms), that site may be
selected for implant.
[0029] Skilled artisans appreciate that a fiducial element may
include one or more of a ventricular event (e.g., a ventricular
pace, a ventricular sense, etc.), an atrial event 32 a maximum
value (e.g., a peak of a QRS complex, a peak of a P-wave, a peak of
a Q wave, a peak of a R wave, etc.), a minimum value, a maximum
slope value (e.g., a maximum slope of an R-wave, etc.), an
amplitude or slope of atrial or ventricular depolarization signal,
a crossing of a predefined threshold, etc. The timing of recurring
fiducial element, or time when the recurring fiducial occurs, may
be used to base the portion of the signal upon. For example, the
start of fiducial element may start the time frame or window to
store a portion of the signal. A 250 ms portion of the signal
starting from a ventricular pace (i.e., the selected fiducial
element) may be stored into memory. As such, a first portion may be
recorded, or stored, from the start of a ventricular pace for 250
ms during a first a cardiac cycle, and a second portion may be
recorded, or stored, from the start of a ventricular pace for 250
ms during a second cardiac cycle that is subsequent to the first
cardiac cycle.
[0030] FIG. 1 is a block diagram illustrating an example
configuration of a system for determining the onsets and offsets of
heart depolarization and repolarizations waves. In the illustrated
example, system 10 includes a device 60, a cardiac electrogram
module 70, and a motion sensing module 80. Device 60 may further
include a processor 72, a memory 74, a peak detection module 76,
and a wave detection module 78.
[0031] Processor 72 may include any one or more of a
microprocessor, a controller, a digital signal processor (DSP), an
application specific integrated circuit (ASIC), a
field-programmable gate array (FPGA), or equivalent discrete or
analog logic circuitry. In some examples, processor 72 may include
multiple components, such as any combination of one or more
microprocessors, one or more controllers, one or more DSPs, one or
more ASICs, or one or more FPGAs, as well as other discrete or
integrated logic circuitry. The functions attributed to processor
72 herein may be embodied as software, firmware, hardware or any
combination thereof. Generally, processor 72 controls cardiac
electrogram module 70, peak detection module 76, wave detection
module 78, and motion sensing module 80 to determine timings of the
onsets and offsets of heart depolarization and repolarizations
waves.
[0032] Memory 74 includes computer-readable instructions that, when
executed by processor 72, causes system 10 and processor 72 to
perform various functions attributed to system 10 and processor 72
herein. Memory 74 may include any volatile, non-volatile, magnetic,
optical, or electrical 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 digital or analog media.
[0033] Generally, cardiac electrogram module 70 is configured sense
or acquire electrical signals from a patient. Cardiac electrogram
module 70 is electrically coupled to one or more electrodes 2, 4,
6, 8, 10, 12, 14 . . . n by one or more leads. In some examples,
the one or more electrodes 2, 4, 6, 8, 10, 12, 14 . . . n may be
external electrodes, e.g., attached to the surface of a patient, or
implanted of various locations within a patient, e.g., on or within
a heart.
[0034] Peak detection module 76 may be configured to determine a
maximum value of a particular signal. For example, peak detection
module 76 may be configured to receive the electrical signal from
cardiac electrogram module 70 and determine the maximum value. In
another example, as illustrated in FIG. 2, peak detection module 76
may be configured to receive a signal from wave detection module 78
and determine a maximum value.
[0035] Wave detection module 78 determines the onsets and offsets
on the heart depolarization and repolarizations waves. Wave
detection module 78 may be configured to receive an electrical
signal. For example, wave detection module 78 may be configured to
receive an electrical signal sensed by cardiac electrogram module
70. Motion sensing module 80 may detect mechanical motion of a
heart, e.g., during contraction of the heart. Motion sensing module
80 may comprise one or more sensors that generate a signal that
varies based on cardiac contraction or motion generally, such as
one or more accelerometers, pressure sensors, impedance sensors, or
flow sensors. Motion sensing module 80 may provide an indication of
the timing of motion, e.g., contraction, to device 60, e.g., to
processor 72. The detected contraction may be contraction of
cardiac tissue at a particular location, e.g., a particular portion
of a ventricular wall.
[0036] In some examples, motion sensing module 80 may be configured
to image the heart, or electrodes, catheters, wires, or other
radio-opaque markers in or on the heart and identify motion
associated with contraction based on images of the heart. In some
examples, motion sensing module 80 may be configured to direct
ultrasound energy toward a patient's heart. Motion sensing module
80 may also be configured to detect any ultrasonic energy deflected
back toward motion sensing module 80 by the patient's heart. In
this manner, motion sensing module 80 may capture information about
the mechanical motion (i.e. the contracting and relaxing of the
ventricles and/or atria) of the heart. Systems and methods for
identifying heart mechanical contractions are described in U.S.
Pat. No. 7,587,074 to Zarkh et al., which issued on Sep. 8, 2009
and is entitled, "METHOD AND SYSTEM FOR IDENTIFYING OPTIMAL IMAGE
WITHIN A SERIES OF IMAGES THAT DEPICT A MOVING ORGAN," and is
incorporated herein by reference in its entirety.
[0037] Processor 72 may determine values of one or more metrics,
such as cardiac intervals or cardiac electromechanical delay, based
on the timing of onset and/or offset of a wave, as determined by
wave detection module 78, and/or the timing of contraction, as
determined by motion sensing module 80. For example, processor 72
may determine QRS width based on an onset and offset of the QRS
complex as identified by wave detection module 78. As another
example, processor 72 may determine a QT interval based on a QRS
onset and T-wave onset identified by wave detection module 78. The
processor may also determine the interval between the onset of
depolarization on a surface ECG lead and the time of local
electrical activation as sensed by a lead or a mapping catheter or
guidewire at a site within the heart. Furthermore, as described in
greater detail below, processor 72 may determine electromechanical
delay based on a QRS onset identified by wave detection module 78
and an indication of the timing of cardiac contraction received
from motion sensing module 80.
[0038] Although in FIG. 1 device 60, module 70, and module 80 are
depicted as separate, in other examples the modules and device may
be combined into fewer separate components. For example, as
illustrated in FIG. 13, all of the functionality of system 10 may
be combined into a single device.
[0039] Furthermore, although processor 72, peak detection module 76
and wave detection module 78 are depicted as separate functional
modules in the example of FIG. 1, their collective functionality
may be provided by any number of physical or logical processing
elements provided by one or more co-located or networked devices.
In one example, peak detection module 76 and wave detection module
78 may be functional modules executed by processor 72. Similarly in
FIG. 2, although the various modules 90, 92, 94, 96, 98, and 99 are
depicted as separate modules in a single device, in other examples
their functionality may be provided by any one or more devices.
[0040] FIG. 2 is a block diagram illustrating an example
configuration of wave detection module 78. In the example of FIG.
2, wave detection module 78 comprises a low-pass filter 90, a
window module 92, a slope module 94, a rectifier module 96, a
smoothing module 98, and a threshold detection module 99.
[0041] Low pass filter 90 may generally be any low-pass filter
designed to reduce or eliminate the high frequency components of
electrical signals. Some examples of low-pass filters embodied in
hardware include capacitive low-pass filters and inductive low-pass
filters. Other low-pass filters may be embodied entirely within
software. In some embodiments, low-pass filter 90 is embodied as a
combination of hardware and software. Low-pass filter 90 may be a
first, second, or higher order filter. In some examples, low-pass
filter 90 comprises multiple filters placed in a succession in
order to create a desired frequency response. In some examples, the
low-pass filter 90 is a linear filter with a maximally flat group
delay or maximally linear phase response. A constant group delay is
a characteristic of phase response of an analog or a digital
filter, which helps preserve the shape of the signal in the
pass-band. In at least one example, the low-pass filter is a Bessel
filter with a cut-off frequency of 15 Hz.
[0042] Window module 92 may generally window received signals. In
some examples, window module 92 may receive cardiac electrograms,
and in further examples, some of the cardiac electrograms may
include a marker or markers indicating one or more points of
interest. Some example of points of interest could be the R-wave,
the P-wave, or any other wave of the cardiac electrogram. In some
examples, peak detection module 76 may detect the locations of
R-waves in a cardiac electrogram, according to techniques that are
well known in the art, for example using a varying threshold. Peak
detection module 76 may then place a marker within the cardiac
electrogram identifying the location of the R-wave. In other
examples, other modules or devices may detect and mark waves in the
cardiac electrogram. In examples where the signal includes at least
one marker, window module 92 may window the received electrical
signal around the marker. For example, window module 92 may
multiply the received electrical signal by zero outside of the area
around the marker and by one inside of the area around the marker.
In this way, window module 92 may modify the received electrical
signal to only contain information in an area around the marker. In
some examples, window module 92 may isolate the QRS complex. In
some examples, window module 92 may window an area of interest of
equal length around the marker, for instance 150 ms before the
marker and 150 ms after the marker. In other examples, the area in
front of the marker may be longer or shorter than the area behind
the marker.
[0043] Slope module 94 may generally determine the slope of a
received electrical signal. Some example techniques for determining
a slope that slope module 94 may use are taking the simple
difference between adjacent points on the received electrical
signal, or determining the first derivative of the received
electrical signal.
[0044] Rectifier module 96 may generally rectify a received
electrical signal. For example, rectifier module 96 may half-wave
rectify the received electrical signal to produce a resulting
signal with information only where the original signal was above
zero. In another example, rectifier module 96 may full-wave rectify
the received electrical signal to produce a resulting signal where
all the negative values of the original signal are now
positive.
[0045] Smoothing module 98 may generally smooth a received
electrical signal. For example, smoothing module 98 may be
configured to increase the values of certain points and decrease
the values of certain points so as to create a smoother signal.
Some example smoothing algorithms include rectangular or
un-weighted sliding average smoothing, triangular smoothing, and
Savitzky-Golay smoothing. The smoothing algorithms may be
implemented through one or more filters. In at least one example,
the smoothing filter is 10-order median filter. In another example,
the smoothing filter is a n-order median filter where n is an
increasing linear function of the sampling frequency used to
digitize the electrogram or electrocardiogram signals.
[0046] Threshold detection module 99 may generally be configured to
determine a threshold and at what points a received electrical
signal crosses a pre-determined threshold. The threshold may be
determined based on a maximum value of the signal received from
smoothing module 98. For example, as illustrated in FIG. 2,
threshold detection module 99 may be configured to receive, from
peak detection module 76, a maximum value of the signal received
from smoothing module 98. Threshold detection module 99 may be
configured to determine a threshold value based on the received
maximum value. For example, threshold detection module 99 may
determine the threshold to be ten percent, fifteen percent, twenty
percent, or more of the maximum value. Ultimately, threshold
detection module 98 may determine the onsets and offsets of heart
depolarization and repolarizations waves based on at which points
of a received electrical signal cross a threshold.
[0047] FIGS. 3-6 illustrate example cardiac electrogram signals
along with various aspects of the present disclosure. For example,
FIG. 3 illustrates an example cardiac electrogram 502 that may be
passed to wave detection module 78. FIG. 4 illustrates a cardiac
electrogram 502 along with wave markers 504. In the example of FIG.
4, wave markers 504 are R-wave markers. FIG. 5 also depicts an
example cardiac electrogram 502 and R-wave markers 504. FIG. 5 also
depicts example windows 506 that wave detection module 78, e.g.
through window module 92, may generate about the wave markers 504.
In the example of FIG. 5, windows 506 are configured to generally
include the QRS complexes and isolate the QRS complexes from the
whole cardiac electrogram, e.g. exclude other waves such as the
P-wave and T-wave. In other examples, the windows 506 may be
configured to generally include P or T-waves and isolate those
waves from the whole cardiac electrogram. FIG. 6 further
illustrates an example cardiac electrogram 502. FIG. 6 also
illustrates the points that wave detection module 78 has determined
are the onset of the waves (more specifically, in the example
illustrated in FIG. 6, the onset of the QRS waves).
[0048] FIGS. 7 and 8 illustrate example cardiac electrograms
combined with example heart mechanical contraction information. For
example, FIG. 7 depicts an example surface ECG signal 702 along
with a cardiac contraction curve 704. Cardiac contraction curve 704
illustrates the contraction of a local point on the heart with
respect to time. The cardiac contraction curve may be a signal
generated by any of the sensors discussed above, for example
accelerometers, pressure sensors, impedance sensors, or flow
sensors associated with motion sensing module 80. In other
examples, the cardiac contraction curve may be generated by the
techniques described in the U.S. Pat. No. 7,587,074 to Zarkh et
al., which issued on Sep. 8, 2009 and is entitled, "METHOD AND
SYSTEM FOR IDENTIFYING OPTIMAL IMAGE WITHIN A SERIES OF IMAGES THAT
DEPICT A MOVING ORGAN," incorporated herein. In still other
examples, the cardiac contraction curve may be generated by sensors
within the tip of an intracardiac electrode. For example, the tip
of a cardiac electrode may contain one or more motion sensors which
generates a signal as the tip of the electrode moves in relation to
the region of the heart in which it is implanted.
[0049] Also depicted in FIG. 7 are the timing of the detected onset
of depolarization of the heart from the surface ECG 706 and the
timing of the local cardiac contraction 708. The delay between the
onset of depolarization 706 from the surface ECG and the timing of
local cardiac contraction 708 may be described as the global
electromechanical delay 710. As will be described in greater detail
in FIGS. 9-10, measuring the global electromechanical delay 710
delay at various locations on the heart may help physicians to
select potential intracardiac lead implant sites.
[0050] FIG. 8 depicts an example unipolar cardiac electrogram
signal 752 from an electrode at a localized position on or within a
heart, along with a cardiac contraction curve 754 from the same
localized position on or within the heart. FIG. 8 also depicts the
timing of the detected onset of depolarization of the heart at the
localized position 756 and the timing of the local cardiac
contraction 758. In contrast to FIG. 7, FIG. 8 displays the
difference in timing between the local depolarization of the heart
756 and the timing of the local cardiac contraction 758 as the
local electromechanical delay 760 or local electromechanical
latency 760. The local electromechanical delay 760 differs from the
global electromechanical delay 710 in that local electromechanical
delay 760 measures the differences in timings both at the localized
heart tissue and the global electromechanical delay 710 measures
the difference in timings between the depolarization 706 detected
at the surface ECG and the local mechanical contraction 708.
[0051] FIG. 9 is a flow diagram describing an example method for
selecting an implant site for an intracardiac lead. In the example
method, a system, such as system 10 of FIG. 1, may determine the
intrinsic global electromechanical delay at a plurality of
potential intracardiac lead implant sites. To determine the
intrinsic global electromechanical delay, a system may determine
the timing of a detected onset of depolarization from a surface ECG
and a timing of cardiac contraction at various locations on the
heart during an intrinsic heart rhythm. The difference between the
timings is the global electromechanical delay (800). Then, in the
example technique, a system, e.g., processor 72, or a user of the
system, may select candidate intracardiac lead implant sites as
sites that have a global electromechanical delay above a certain
threshold (802). Finding particular candidate sites with a long
global electromechanical delay may indicate that the particular
location of the heart contracts late and may be the reason for
dyssynchrony of cardiac wall motion. Selecting an implant site to
provide pacing on or near that site may enhance the effectiveness
of the electrical pacing therapy to restore cardiac synchrony.
[0052] In the example technique, processor 72 may then determine
the local electromechanical delay of the selected candidate implant
sites during an intrinsic heart rhythm (804). To determine the
local electromechanical delay, processor 72 may determine the
timing of a detected onset of depolarization from an electrogram
taken at the potential implant site and a timing of the local
cardiac contraction at the potential implant sites. The local
electromechanical delay is the difference between the determined
timings. Then, in the example technique, processor 72 may
automatically select a subset of potential implant sites as sites
that have a local electromechanical delay less than a threshold
(806). In other examples, a user may manually select the potential
implants based on information from processor 72. Candidate implant
sites that have a long local electromechanical delay may indicate a
region of scarred or non-viable or otherwise non-conductive tissue.
Implanting an intracardiac lead at those locations may reduce the
effectiveness of the electrical stimulation therapy.
[0053] Processor 72 may then deliver electrical pacing stimulus to
the heart at the potential implant sites (808). Processor 72 may
measure various metrics such as global or local electromechanical
delay during pacing at each potential implant site. In the example
technique, processor 72 may then automatically select one or more
implant sites based on the reduction of a metric during pacing
compared to the intrinsic baseline. In other examples, a user may
select one or more implant sites based on information from
processor 72. For example, processor 72, or a user, may select one
or more implant sites based on the reduction of local
electromechanical, global electromechanical delay, or cardiac
dyssynchrony, which is a measure of the distribution and dispersion
(e.g. range, standard deviation, etc.) of global or local
electromechanical delays at various cardiac sites. In other example
techniques, processor 72 or a user may select other parameters
based on the global and/or local electromechanical delay. For
example, processor 72 may also vary parameters of the pacing, such
as A-V delay, V-V delay, and pacing electrode configuration, and
select a particular pacing electrode configuration or pacing
intervals for cardiac resynchronization therapy based on the
metric. In other examples, a user may ultimately select the pacing
electrode configuration or pacing intervals based on the
metric.
[0054] FIG. 10 is flow diagram illustrating another example
technique for selecting an implant site for an intracardiac lead.
In the example technique, a system, such as system 10, may
determine a global electromechanical delay at a potential implant
site during an intrinsic heart rhythm (850). In the example
technique, a system may then determine local electromechanical
delay at the same potential implant site during an intrinsic heart
rhythm (852). A system may then determine a baseline
electromechanical dyssynchrony index for an intrinsic heart rhythm
(854). A system may determine the baseline electromechanical
dyssynchrony index by comparing the differences between the global
and local electromechanical delays during the intrinsic heart
rhythm.
[0055] In the example technique, a system may then determine a
global electromechanical delay at the same potential implant site
during the delivery of electrical pacing therapy (856). In the
example technique, a system may then determine local
electromechanical delay at the same potential implant site during
the delivery of electrical pacing therapy (858). A system may then
determine an electromechanical dyssynchrony index during pacing
therapy (860).
[0056] In the example technique, a system may then determine the
percentage change between the baseline electromechanical
dyssynchrony index and the electromechanical dyssynchrony index
determined during pacing therapy (862). A system may then determine
if there was a reduction from the baseline dyssynchrony index at
the tested potential implant site above a threshold percentage
(864). If the system determines that the performance of the pacing
at the potential implant site did produce a reduction in the
baseline electromechanical dyssynchrony index above a threshold
percentage (YES of 864), the system may select that implant site
(866) for intracardiac lead implantation. In some examples, a
processor of the system, such as processor 72, may automatically
select the implant site according to the described techniques. In
other examples, a user, based on information from a processor may
manually select the implant site according to the described
techniques. If the system determines that pacing at the potential
site did not reduce the baseline electromechanical dyssynchrony
index by a threshold percentage amount (NO of 864), the system may
check to see if there are other potential lead implant sites to
check (868). If there are still other implant sites to check (YES
of 868), in the example technique, a system may change the
potential lead implant site (870) and return to step 856. If there
are no more potential lead implant sites to check (NO of 868), a
system may select the implant site with the greatest reduction in
the baseline electromechanical dyssynchrony index as the preferred
intracardiac lead implant site.
[0057] In another example, the system may detect the time-interval
from delivery of pace at a localized region within the heart to the
onset of depolarization on a surface ECG lead, with the pace
delivered at maximum pacing voltage (.about.6V to ensure that
maximum energy is delivered during pacing) and at a short
atrio-ventricular (A-V) interval (.ltoreq.60 ms). If this time
interval exceeds a certain threshold, then the system will indicate
that particular area is not a suitable site for implanting the
pacing lead. This is because a long time delay between delivery of
local pace (at maximum energy) and onset of global depolarization
on surface ECG indicates that the substrate of that area in the
heart may be non-viable or otherwise not be a suitable site for
implanting the pacing lead, e.g., comprised of scar tissue. FIG. 14
illustrates an example of the time-delay between the delivery of
pacing and the onset of depolarization. FIG. 14 illustrates an
example ECG signal 990. Arrow 992 points to the point in time when
a patient received pacing at a localized region of the heart. Arrow
994 points to the determined point in time of the onset of the
depolarization wave. The onset of the depolarization wave may be
found, for example, according the techniques described in this
disclosure. Time period 996 is the difference in time between the
beginning of pacing and the onset of the depolarization wave at a
localized region of the heart. The time period 996 may also be
termed the local electrical-electrical delay.
[0058] FIGS. 11-13 are conceptual diagrams illustrating an example
system 910 that determines the onset and offset points of heart
depolarization and repolarization waves of patient 914 according to
the techniques described herein. As with the previously described
system, in one example, system 910 may detect the onset and offset
points of heart depolarization and repolarization waves in order to
select a preferred location for implanting an intracardiac lead. In
other examples, system 910 may detect the onset and offset points
of heart depolarization and repolarization waves in order to select
other parameters based on the electromechanical delay. For example,
the system may select a particular pacing electrode configuration
or pacing intervals for cardiac resynchronization therapy. In
another example, with multipolar leads offering choices of more
than one pacing electrode (cathode) in the ventricle, the
system/device may automatically pace from each of the pacing
electrodes at maximum pacing voltage and at a nominal
atrio-ventricular delay (.about.100 ms) and measure onsets and
offsets of the resulting depolarization waveforms on a far-field
electrogram or on a leadless ECG or on a surface ECG lead, and
choose the pacing electrode which produces the minimum difference
between the offset of the local electrogram and the corresponding
far-field onset, for delivery of cardiac resynchronization therapy.
Alternatively, the pacing electrode which produces the narrowest
far-field electrogram or surface ECG signal calculated as the
difference between the offset and onset could be chosen. As
illustrated in example diagram FIG. 11A, a system 910 includes
implantable medical device (IMD) 916, which is connected to leads
918, 920, and 922, and communicatively coupled to a programmer 924.
IMD 916 senses electrical signals attendant to the depolarization
and repolarization of heart 912, e.g., a cardiac EGM, via
electrodes on one or more of leads 918, 920 and 922 or a housing of
IMD 916. IMD 916 also delivers therapy in the form of electrical
signals to heart 912 via electrodes located on one or more leads
918, 920, and 922 or a housing of IMD 916, such pacing,
cardioversion and/or defibrillation pulses. IMD 916 may include or
be coupled to various sensors, such as one or more accelerometers,
for detecting other physiological parameters of patient 914, such
as activity or posture.
[0059] In some examples, programmer 924 takes the form of a
handheld computing device, computer workstation, or networked
computing device that includes a user interface for presenting
information to and receiving input from a user. A user, such as a
physician, technician, surgeon, electrophysiologist, or other
clinician, may interact with programmer 924 to communicate with IMD
916. For example, the user may interact with programmer 924 to
retrieve physiological or diagnostic information from IMD 916. A
user may also interact with programmer 924 to program IMD 916,
e.g., select values for operational parameters of the IMD.
[0060] IMD 916 and programmer 924 may communicate via wireless
communication using any techniques known in the art. Examples of
communication techniques may include, for example, low frequency or
radiofrequency (RF) telemetry, but other techniques are also
contemplated. In some examples, programmer 924 may include a
programming head that may be placed proximate to the patient's body
near the IMD 916 implant site in order to improve the quality or
security of communication between IMD 916 and programmer 924. In
other examples, programmer 924 may be located remotely from IMD
916, and communicate with IMD 916 via a network.
[0061] The techniques for identifying onsets and/or offsets of
cardiac electrogram waves may be performed by IMD 916, e.g., by a
processor of IMD 916, based on one or more cardiac electrograms
sensed by the IMD. In other examples, as described previously, some
or all of the functions ascribed to IMD 916 or a processor thereof
may be performed by one or more other devices, such as programmer
294 or a workstation (not shown), or a processor thereof. For
example, programmer 924 may process EGM signals received from IMD
916 and/or cardiac mechanical contraction information to according
to the techniques described herein. Furthermore, although described
herein with respect to an IMD, in other examples, the techniques
described herein may be performed by or implemented in an external
medical device, which may be coupled to a patient via percutaneous
or transcutaneous leads.
[0062] FIGS. 11B and 11C are conceptual diagrams illustrating
example systems for measuring body-surface potentials and, more
particularly, torso-surface potentials. In one example illustrated
in FIG. 11B, sensing device 1000A, comprising a set of electrodes
1002A-F (generically "electrodes 1002") and strap 1008, is wrapped
around the torso of patient 914 such that the electrodes surround
heart 912. As illustrated in FIG. 11B, electrodes 1002 may be
positioned around the circumference of patient 914, including the
posterior, lateral, and anterior surfaces of the torso of patient
914. In other examples, electrodes 1002 may be positioned on any
one or more of the posterior, lateral, and anterior surfaces of the
torso. Electrodes 1002 may be electrically connected to a
processing unit such as device 60 via wired connection 1004. Some
configurations may use a wireless connection to transmit the
signals sensed by electrodes 1002 to device 60, e.g., as channels
of data.
[0063] Although in the example of FIG. 11B sensing device 1000A
comprises strap 1008, in other examples any of a variety of
mechanisms, e.g., tape or adhesives, may be employed to aid in the
spacing and placement of electrodes 1002. In some examples, strap
1008 may comprise an elastic band, strip of tape, or cloth. In some
examples, electrodes 1002 may be placed individually on the torso
of patient 914.
[0064] Electrodes 1002 may surround heart 912 of patient 914 and
record the electrical signals associated with the depolarization
and repolarization of heart 912 after the signals have propagated
through the torso of patient 914. Each of electrodes 1002 may be
used in a unipolar configuration to sense the torso-surface
potentials that reflect the cardiac signals. Device 60 may also be
coupled to a return or indifferent electrode (not shown) which may
be used in combination with each of electrodes 1002 for unipolar
sensing. In some examples, there may be 12 to 16 electrodes 1002
spatially distributed around the torso of patient 914. Other
configurations may have more or fewer electrodes 1002.
[0065] Processing unit 60 may record and analyze the torso-surface
potential signals sensed by electrodes 1002. As described herein,
device 60 may be configured to provide an output to a user. The
user may make a diagnosis, prescribe CRT, position therapy devices,
e.g., leads, or adjust or select treatment parameters based on the
indicated output.
[0066] In some examples, the analysis of the torso-surface
potential signals by device 60 may take into consideration the
location of electrodes 1002 on the surface of the torso of patient
914. In such examples, device 60 may be communicatively coupled to
an motion sensing module 80 such as a programmer, which may provide
an image that allows device 60 to determine coordinate locations of
each of electrodes 1002 on the surface of patient 914. Electrodes
1002 may be visible, or made transparent through the inclusion or
removal of certain materials or elements, in the image provided by
motion sensing module 80.
[0067] FIG. 11C illustrates an example configuration of a system
that may be used to evaluate cardiac response in heart 912 of
patient 914. The system comprises a sensing device 10008, which may
comprise vest 1006 and electrodes 1002 A-ZZ (generically
"electrodes 1002"), a device 60, and imaging system 501. Device 60
and imaging system 501 may perform substantially as described above
with respect to FIG. 11A. As illustrated in FIG. 11C, electrodes
1002 are distributed over the torso of patient 914, including the
anterior, lateral, and posterior surfaces of the torso of patient
914.
[0068] Sensing device 1000B may comprise a fabric vest 1006 with
electrodes 1002 attached to the fabric. Sensing device 1000B may
maintain the position and spacing of electrodes 1002 on the torso
of patient 914. Sensing device 1000B may be marked to assist in
determining the location of electrodes 1002 on the surface of the
torso of patient 914. In some examples, there may be 150 to 256
electrodes 1002 distributed around the torso of patient 914 using
sensing device 1000B, though other configurations may have more or
fewer electrodes 1002.
[0069] The ECG data is mapped to a generic, graphical model of a
patient's torso and/or heart and a graphical display is produced on
a graphical user interface without taking an actual image, such as
an MRI or CT image, from the patient. The resolution of the ECG
data mapped to a graphical anatomical model depends on the number
and spacing of surface electrodes 1002 used. In some examples,
there may be 12 to 16 electrodes spatially distributed around the
torso of patient 914. Other configurations may have more or fewer
electrodes. In one embodiment, a minimum number of electrodes
includes twelve electrodes arranged in two rows extending along the
posterior torso and twelve electrodes arranged in two rows
extending along the anterior torso for a total of twenty-four
electrodes, which may be equally distributed circumferentially
around the torso.
[0070] FIG. 12 is a conceptual diagram illustrating IMD 916 and
leads 918, 920, and 922 of system 910 in greater detail. In the
illustrated example, bipolar electrodes 940 and 942 are located
adjacent to a distal end of lead 918. In addition, bipolar
electrodes 944 and 946 are located adjacent to a distal end of lead
920, and bipolar electrodes 948 and 950 are located adjacent to a
distal end of lead 922.
[0071] In the illustrated example, electrodes 940, 944 and 948 take
the form of ring electrodes, and electrodes 942, 946 and 950 may
take the form of extendable helix tip electrodes mounted
retractably within insulative electrode heads 952, 954 and 956,
respectively. Leads 918, 920, 922 also include elongated electrodes
962, 964, 966, respectively, which may take the form of a coil. In
some examples, each of the electrodes 940, 942, 944, 946, 948, 950,
962, 964 and 966 is electrically coupled to a respective conductor
within the lead body of its associated lead 918, 920, 922, and
thereby coupled circuitry within IMD 916.
[0072] In some examples, IMD 916 includes one or more housing
electrodes, such as housing electrode 904 illustrated in FIG. 12,
which may be formed integrally with an outer surface of
hermetically-sealed housing 908 of IMD 916 or otherwise coupled to
housing 908. In some examples, housing electrode 904 is defined by
an uninsulated portion of an outward facing portion of housing 908
of IMD 916. Other division between insulated and uninsulated
portions of housing 908 may be employed to define two or more
housing electrodes. In some examples, a housing electrode comprises
substantially all of housing 908.
[0073] As described in further detail with reference to FIG. 13,
housing 908 encloses a signal generator that generates therapeutic
stimulation, such as cardiac pacing, cardioversion and
defibrillation pulses, as well as a sensing module for sensing
electrical signals attendant to the depolarization and
repolarization of heart 912. Housing 908 may also enclose a wave
detection module that detects the onsets and offsets of heart
depolarization and repolarization waves. The wave detection module
may be enclosed within housing 908. Alternatively, the wave
detection module may housed in a remote piece of equipment, such as
programmer 924 or a workstation (not shown) and communicate with
the IMD 916 through wireless communication.
[0074] IMD 916 senses electrical signals attendant to the
depolarization and repolarization of heart 912 via electrodes 904,
940, 942, 944, 946, 948, 950, 962, 964 and 966. IMD 916 may sense
such electrical signals via any bipolar combination of electrodes
940, 942, 944, 946, 948, 950, 962, 964 and 966. Furthermore, any of
the electrodes 940, 942, 944, 946, 948, 950, 962, 964 and 966 may
be used for unipolar sensing in combination with housing electrode
904.
[0075] In some examples, IMD 916 delivers pacing pulses via bipolar
combinations of electrodes 940, 942, 944, 946, 948 and 950 to
produce depolarization of cardiac tissue of heart 912. In some
examples, IMD 16 delivers pacing pulses via any of electrodes 940,
942, 944, 946, 948 and 950 in combination with housing electrode
904 in a unipolar configuration. Furthermore, IMD 916 may deliver
cardioversion or defibrillation pulses to heart 12 via any
combination of elongated electrodes 962, 964, 966, and housing
electrode 904.
[0076] The illustrated numbers and configurations of leads 918,
920, and 922 and electrodes are merely examples. Other
configurations, i.e., number and position of leads and electrodes,
are possible. In some examples, system 910 may include an
additional lead or lead segment having one or more electrodes
positioned at different locations in the cardiovascular system for
sensing and/or delivering therapy to patient 914. For example,
instead of or in addition to intracardiac leads 918, 920 and 922,
system 910 may include one or more epicardial or subcutaneous leads
not positioned within the heart. In some examples, the subcutaneous
leads may sense a subcutaneous cardiac electrogram, for example the
far-field electrogram between the SVC coil and the can. The
subcutaneous cardiac electrogram may substitute for the surface ECG
in determining the global electromechanical delay.
[0077] FIG. 13 is a block diagram illustrating an example
configuration of IMD 916. In the illustrated example, IMD 916
includes a processor 970, memory 972, signal generator 974, sensing
module 976, telemetry module 978, motion sensing module 980, wave
detection module 982 and peak detection module 984. Memory 972
includes computer-readable instructions that, when executed by
processor 970, causes IMD 916 and processor 970 to perform various
functions attributed to IMD 916 and processor 970 herein. Memory
972 may include any volatile, non-volatile, magnetic, optical, or
electrical 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 digital or
analog media.
[0078] Processor 970 may include any one or more of a
microprocessor, a controller, a digital signal processor (DSP), an
application specific integrated circuit (ASIC), a
field-programmable gate array (FPGA), or equivalent discrete or
analog logic circuitry. In some examples, processor 970 may include
multiple components, such as any combination of one or more
microprocessors, one or more controllers, one or more DSPs, one or
more ASICs, or one or more FPGAs, as well as other discrete or
integrated logic circuitry. The functions attributed to processor
970 herein may be embodied as software, firmware, hardware or any
combination thereof. Generally, processor 970 controls signal
generator 974 to deliver stimulation therapy to heart 912 of
patient 914 according to a selected one or more of therapy programs
or parameters, which may be stored in memory 972. As an example,
processor 970 may control signal generator 974 to deliver
electrical pulses with the amplitudes, pulse widths, frequency, or
electrode polarities specified by the selected one or more therapy
programs.
[0079] Signal generator 974 is configured to generate and deliver
electrical stimulation therapy to patient 912. As shown in FIG. 13,
signal generator 974 is electrically coupled to electrodes 94, 940,
942, 944, 946, 948, 950, 962, 964, and 966, e.g., via conductors of
the respective leads 918, 920, and 922 and, in the case of housing
electrode 904, within housing 908. For example, signal generator
974 may deliver pacing, defibrillation or cardioversion pulses to
heart 912 via at least two of electrodes 94, 940, 942, 944, 946,
948, 950, 962, 964, and 966. In other examples, signal generator
974 delivers stimulation in the form of signals other than pulses,
such as sine waves, square waves, or other substantially continuous
time signals.
[0080] Signal generator 974 may include a switch module (not shown)
and processor 970 may use the switch module to select, e.g., via a
data/address bus, which of the available electrodes are used to
deliver the electrical stimulation. The switch module may include a
switch array, switch matrix, multiplexer, or any other type of
switching device suitable to selectively couple stimulation energy
to selected electrodes. Electrical sensing module 976 monitors
electrical cardiac signals from any combination of electrodes 904,
940, 942, 944, 946, 948, 950, 962, 964, and 966. Sensing module 976
may also include a switch module which processor 970 controls to
select which of the available electrodes are used to sense the
heart activity, depending upon which electrode combination is used
in the current sensing configuration.
[0081] Sensing module 976 may include one or more detection
channels, each of which may comprise an amplifier. The detection
channels may be used to sense the cardiac signals. Some detection
channels may detect events, such as R-waves or P-waves, and provide
indications, such as wave markers, of the occurrences of such
events to processor 970. One or more other detection channels may
provide the signals to an analog-to-digital converter, for
conversion into a digital signal for processing or analysis by
processor 970.
[0082] For example, sensing module 976 may comprise one or more
narrow band channels, each of which may include a narrow band
filtered sense-amplifier that compares the detected signal to a
threshold. If the filtered and amplified signal is greater than the
threshold, the narrow band channel indicates that a certain
electrical cardiac event, e.g., depolarization, has occurred.
Processor 970 then uses that detection in measuring frequencies of
the sensed events.
[0083] In one example, at least one narrow band channel may include
an R-wave or P-wave amplifier. In some examples, the R-wave and
P-wave amplifiers may take the form of an automatic gain controlled
amplifier that provides an adjustable sensing threshold as a
function of the measured R-wave or P-wave amplitude. Examples of
R-wave and P-wave amplifiers are described in U.S. Pat. No.
5,117,824 to Keimel et al., which issued on Jun. 2, 1992 and is
entitled, "APPARATUS FOR MONITORING ELECTRICAL PHYSIOLOGIC
SIGNALS," and is incorporated herein by reference in its
entirety.
[0084] In some examples, sensing module 976 includes a wide band
channel which may comprise an amplifier with a relatively wider
pass band than the narrow band channels. Signals from the
electrodes that are selected for coupling to this wide-band
amplifier may be converted to multi-bit digital signals by an
analog-to-digital converter (ADC) provided by, for example, sensing
module 976 or processor 970. Processor 970 may analyze the
digitized versions of signals from the wide band channel. Processor
970 may employ digital signal analysis techniques to characterize
the digitized signals from the wide band channel to, for example,
detect and classify the patient's heart rhythm.
[0085] Processor 970 may detect and classify the patient's heart
rhythm based on the cardiac electrical signals sensed by sensing
module 976 employing any of the numerous signal processing
methodologies known in the art. For example, processor 970 may
maintain escape interval counters that may be reset upon sensing of
R-waves by sensing module 976. The value of the count present in
the escape interval counters when reset by sensed depolarizations
may be used by processor 970 to measure the durations of R-R
intervals, which are measurements that may be stored in memory 972.
Processor 970 may use the count in the interval counters to detect
a tachyarrhythmia, such as ventricular fibrillation or ventricular
tachycardia. A portion of memory 972 may be configured as a
plurality of recirculating buffers, capable of holding series of
measured intervals, which may be analyzed by processor 970 to
determine whether the patient's heart 912 is presently exhibiting
atrial or ventricular tachyarrhythmia.
[0086] In some examples, processor 970 may determine that
tachyarrhythmia has occurred by identification of shortened R-R
interval lengths. Generally, processor 970 detects tachycardia when
the interval length falls below 360 milliseconds (ms) and
fibrillation when the interval length falls below 320 ms. These
interval lengths are merely examples, and a user may define the
interval lengths as desired, which may then be stored within memory
972. This interval length may need to be detected for a certain
number of consecutive cycles, for a certain percentage of cycles
within a running window, or a running average for a certain number
of cardiac cycles, as examples.
[0087] In some examples, an arrhythmia detection method may include
any suitable tachyarrhythmia detection algorithms. In one example,
processor 970 may utilize all or a subset of the rule-based
detection methods described in U.S. Pat. No. 5,545,186 to Olson et
al., entitled, "PRIORITIZED RULE BASED METHOD AND APPARATUS FOR
DIAGNOSIS AND TREATMENT OF ARRHYTHMIAS," which issued on Aug. 13,
1996, or in U.S. Pat. No. 5,755,736 to Gillberg et al., entitled,
"PRIORITIZED RULE BASED METHOD AND APPARATUS FOR DIAGNOSIS AND
TREATMENT OF ARRHYTHMIAS," which issued on May 26, 1998. U.S. Pat.
No. 5,545,186 to Olson et al. U.S. Pat. No. 5,755,736 to Gillberg
et al. is incorporated herein by reference in their entireties.
However, other arrhythmia detection methodologies may also be
employed by processor 970 in other examples. For example, EGM
morphology may be considered in addition to or instead of interval
length for detecting tachyarrhythmias.
[0088] Generally, processor 970 detects a treatable
tachyarrhythmia, such as VF, based on the EGM, e.g., the R-R
intervals and/or morphology of the EGM, and selects a therapy to
deliver to terminate the tachyarrhythmia, such as a defibrillation
pulse of a specified magnitude. The detection of the
tachyarrhythmia may include a number of phases or steps prior to
delivery of the therapy, such as first phase, sometimes referred to
as detection, in which a number of consecutive or proximate R-R
intervals satisfies a first number of intervals to detect (NID)
criterion, a second phase, sometimes referred to as confirmation,
in which a number of consecutive or proximate R-R intervals
satisfies a second, more restrictive NID criterion. Tachyarrhythmia
detection may also include confirmation based on EGM morphology or
other sensors subsequent to or during the second phase.
[0089] In the illustrated example, IMD 916 also includes peak
detection module 980, wave detection module 982, and motion sensing
module 984. Peak detection module 980 and wave detection module 982
may be configured and provide the functionality ascribed to peak
detection module 76 and wave detection module 78 herein. Peak
detection module 980 may be configured to determine a maximum value
of a particular signal. For example, peak detection module 980 may
be configured to receive an electrical signal from wave detection
module 982 or processor 970 and determine a maximum value of the
received signal. Peak detection module 980 may, in some examples,
comprise a narrow-band channel of sensing module 976 that is
configured to detect R-waves, P-waves, or T-waves in cardiac
electrogram signals, e.g., using an amplifier with automatically
adjusting threshold.
[0090] Generally, wave detection module 982 determines the onsets
and offsets on the heart depolarization and repolarizations waves.
Wave detection module 982 may be similar to the wave detection
module described previously, e.g. wave detection module 78, and
more accurately described in FIG. 2. For example, wave detection
module may include a low-pass filter, a window module, a slope
module, a rectifier module, a smoothing module, and a threshold
detection module. Wave detection module 982 may perform
substantially similar to the wave detection module described
previously in this application.
[0091] Peak detection module 980 and wave detection module 982 may
receive a cardiac electrogram from sensing module 976, e.g., from a
wide-band channel of the sensing module. In some examples, the
cardiac electrogram may be a far-field cardiac electrogram, e.g.,
between superior vena cava coil 766 and housing electrode 904. A
far-field cardiac electrogram may be used in the manner described
herein with respect to a surface ECG, e.g., to determine a global
electromechanical delay. In some examples, the cardiac electrogram
may be a unipolar cardiac electrogram between housing electrode 906
and any of electrodes 942, 944, 946 and 950. The unipolar cardiac
electrogram may be received from sensing module 976, e.g., via a
wide-band channel of the sensing module, and may be used in the
manner described herein with respect to local cardiac electrogram
signals, e.g., to determine local electromechanical delays.
[0092] Motion sensing module 984 may sense the mechanical
contraction of the heart, e.g., at one or more cardiac sites.
Motion sensing module 984 may be electrically coupled to one or
more sensors that generate a signal that varies based on cardiac
contraction or motion generally, such as one or more
accelerometers, pressure sensors, impedance sensors, or flow
sensors. The detected contraction may be contraction of cardiac
tissue at a particular location, e.g., a particular portion of a
ventricular wall.
[0093] Although processor 970 and wave detection module 982 are
illustrated as separate modules in FIG. 13, processor 970 and wave
detection module 982 may be incorporated in a single processing
unit. Wave detection module 982, and any of its components, may be
a component of or module executed by processor 970.
[0094] Telemetry module 978 includes any suitable hardware,
firmware, software or any combination thereof for communicating
with another device, such as programmer 924 (FIG. 11). In some
examples, programmer 924 may include a programming head that is
placed proximate to the patient's body near the IMD 916 implant
site, and in other examples programmer 924 and IMD 916 may be
configured to communicate using a distance telemetry algorithm and
circuitry that does not require the use of a programming head and
does not require user intervention to maintain a communication
link. Under the control of processor 970, telemetry module 978 may
receive downlink telemetry from and send uplink telemetry to
programmer 924 with the aid of an antenna, which may be internal
and/or external. In some examples, processor 970 may transmit
cardiac signals produced by sensing module 976 and/or signals
generated by heart sound sensor 982 to programmer 924. Processor
970 may also generate and store marker codes indicative of
different cardiac events that sensing module 976 or heart sound
analyzer 980 detects, and transmit the marker codes to programmer
924. An example IMD with marker-channel capability is described in
U.S. Pat. No. 4,374,382 to Markowitz, entitled, "MARKER CHANNEL
TELEMETRY SYSTEM FOR A MEDICAL DEVICE," which issued on Feb. 15,
1983 and is incorporated herein by reference in its entirety.
Information which processor 970 may transmit to programmer 924 via
telemetry module 978 may also include indications of treatable
rhythms, and indications of non-treatable rhythms in which the EGM
based indication indicated that the rhythm was treatable and the
heart sound based indication indicated that the rhythm was
non-treatable. Such information may be included as part of a marker
channel with an EGM.
[0095] The flow diagram depicted in FIG. 15 discloses a
computer-implemented method 1100 that determines onsets and/or
offsets of cardiac depolarization waves without using a
threshold-based detection algorithm. Detection of onset of a
depolarization wave is desirable since CRT may be optimized. By way
of illustration, CRT data such as q-LV times and activation times
are automatically determined, which is useful when implanting a
left ventricular lead. For example, a programmer can be set to
automatically check if the local q-LV time is greater than a
predetermined value (e.g. 90-100 ms). If the local q-LV time is
greater than the predetermined value, the local q-LV time is
displayed on the graphical user interface of the programmer to the
user (e.g. physician or implanter) so that the left ventricular
lead can be properly positioned. Generally, sites with
q-LV>90-100 ms sites are preferable for LV lead implantation as
opposed to sites with a shorter q-LV.
[0096] Implementation of method 1100 requires a plurality of
body-surface electrodes such as an ECG belt or vest be placed
around the torso of the patient. An exemplary ECG belt or vest is
described in U.S. patent application Ser. No. 13/462,404, filed May
2, 2012, entitled "Assessing Intra-Cardiac Activation Patterns And
Electrical Dyssynchrony" and assigned to the assignee of the
present invention, the disclosure of which is incorporated by
reference in its entirety herein. After the vest or belt is secured
around the patient's torso, the programmer is activated. Exemplary
programmers that can be used to acquire signals from implanted and
surface electrodes includes the Medtronic Carelink Programmer Model
2090 and the Model 2290 Analyzer or the CARELINK ENCORE.TM..
Medtronic Vitatron Reference Manual CARELINK ENCORE.TM. (2013)
available at
http://manuals.medtronic.com/manuals/main/as/en/manual, the
disclosure of which is incorporated by reference in its
entirety.
[0097] Far-field EGMs, ECG, or ECG-like signals are acquired from
an electrode that is the greatest distance away from the pacing
electrode. If an IMD is implanted, electrodes that can produce far
field signals include superior vena cava (SVC) electrode-pulse
generator housing (also referred to as a "can"), right ventricle
(RV) coil-can etc.).
[0098] Method 1100 starts at operation 1102 in which a baseline
rhythm is acquired from a plurality of body-surface electrodes and
then stored into memory. The baseline rhythm includes fiducials
such as an atrial wave marker and a ventricular wave marker. The
atrial wave marker is associated with an atrial event (e.g., an
atrial sense, etc.), while a ventricular wave marker is associated
with a ventricular event (e.g., a ventricular sense, etc.). Each
marker can be displayed to a user on a graphical user interface of
a computer such as a programmer.
[0099] At block 1104, a pre-specified window is set. The
pre-specified window can be defined as extending from the atrial
marker to the ventricular marker, an example of which is shown
along the ECG signal in FIG. 16A. The y-axis is in millivolts (mv)
and the x-axis is time in milliseconds (ms) for FIG. 16A.
[0100] A low pass filter is then applied at block 1106 to the ECG
signal within the pre-specified window. The low-pass filter can be
a Bessel filter with a cut-off frequency of 15 Hz, 20 Hz or a
frequency value between 15 Hz and 20 Hz. The signal(s) acquired
from the plurality of surface electrodes and/or the electrodes
associated with the implantable medical device is passed through
the low pass filter, which causes the removal of any spurious
high-frequency artifacts or components from the far-field ECG-like
signal.
[0101] A rectified slope of the signal within the window is
determined at block 1108 using module 96 depicted in FIG. 2.
Rectification of a signal can be performed by any known method. At
block 1110, a time point (t1) (shown in FIG. 16A) is determined
such that the rectified slope exceeds 10% of a maximum value of the
rectified slope. A point of onset of a depolarization complex in
the signal is determined at block 1112. The point of onset of the
depolarization signal requires the radii of the curvature of the
signal within the pre-specified window to be determined, as shown
in FIG. 16B. The radii is plotted along a y-axis in curvature
(curvature-mV) units and a x-axis in time of milliseconds. The
radius of the curvature equation used to plot FIG. 16B is defined
as r=|y''|/(1+|y'|.sup.2).sup.(3/2) in which y'' and y' are the
double and single derivatives of respectively. y is the signal
acquired from surface electrodes and/or electrodes associated with
an implanted medical device. The first and second derivatives of
the signal, represented by y=f(t), can be determined using a
variety of known methods. Firmware or other computer instructions,
stored in memory, can determine the derivatives of y(t). For
example, the first derivative, y', can be determined by repeatedly
calculating the slope between two different points along the
signal. The second derivative, y'' can be similarly calculated but
instead of using y(t), different points along y' curve are used. In
another embodiment a simplified expression tracking the curvature
may be used like r.apprxeq.|y''|/(1+|y'|.sup.2) which makes it
easier from the computational standpoint, eliminating the need of
computing square roots. The simplified curvature equation
r.apprxeq.|y''|/(1+|y'|2), (the radii shown by the dashed line in
FIG. 16B), can also be used to compute an index that tracks the
curvature.
[0102] In particular, the algorithm searches radii along points in
the curve in order to locate the greatest curvature (shown in FIGS.
16A-16B) within a window of pre-specified width and ending on the
maximum peak, or minimum valley. The radius of the curvature is
solely determined for the signal within the pre-specified window.
In one or more other embodiments involving biphasic signals, the
algorithm is configured to search for the greatest curvature within
a window of pre-specified width and ending on the maximum peak, or
minimum valley, whichever is greater in magnitude between the
maximum and minimum peaks.
[0103] The onset of depolarization is identified by the point
associated with the maximum curvature within the search window, as
shown in FIGS. 16A-16B. In particular, the point of onset occurs at
a largest curvature in the signal within the window from Vs-100 ms
to t1. The largest curvature in the signal occurs at the highest
value at points in which a sharp deflection exists which is
indicative of the onset of depolarization on an ECG-like signal.
After determining the onset of depolarization, the user can make
appropriate adjustments to the implantable medical device in order
to optimize CRT. While the techniques described in FIG. 15 have
been applied to the onset of depolarization, the same principles
can be applied to detection of the onset of repolarization signals
such as T waves. As applied to repolarization signals, useful data
can be obtained for adjusting Q-T intervals for CRT.
[0104] The stable and reliable algorithm, described in method 1100,
detects QRS onset with minimum inputs or manipulation from the
user. Additionally, the algorithm may be incorporated within an IMD
(e.g. CRT device) for marking the onset of QRS waves on leadless
ECG or ECG or other far-field ECG-like signals. By incorporating
the algorithm into the IMD, measurements of electrical activation
times are automated with respect to the onset of QRS waves and/or T
waves.
[0105] The techniques described in this disclosure, including those
attributed to IMD wave detection module 80, programmer 24, or
various constituent components, may be implemented, at least in
part, in hardware, software, firmware or any combination thereof.
For example, various aspects of the techniques may be implemented
within one or more processors, including one or more
microprocessors, digital signal processors (DSPs), application
specific integrated circuits (ASICs), field programmable gate
arrays (FPGAs), or any other equivalent integrated or discrete
logic circuitry, as well as any combinations of such components,
embodied in programmers, such as physician or patient programmers,
stimulators, image processing devices or other devices. The term
"processor" or "processing circuitry" may generally refer to any of
the foregoing logic circuitry, alone or in combination with other
logic circuitry, or any other equivalent circuitry.
[0106] Such hardware, software, firmware may be implemented within
the same device or within separate devices to support the various
operations and functions described in this disclosure. In addition,
any of the described units, modules or components may be
implemented together or separately as discrete but interoperable
logic devices. Depiction of different features as modules or units
is intended to highlight different functional aspects and does not
necessarily imply that such modules or units must be realized by
separate hardware or software components. Rather, functionality
associated with one or more modules or units may be performed by
separate hardware or software components, or integrated within
common or separate hardware or software components.
[0107] There are a variety of other embodiments that can be
employed for the pre-specified window used in FIG. 15. For example,
the pre-specified window can be set to begin at an atrial wave
marker and extend a certain length of time or to another marker. In
yet another embodiment, the pre-specified window can be set to
begin at a ventricular wave marker and extend a certain length of
time or to another marker.
[0108] When implemented in software, the functionality ascribed to
the systems, devices and techniques described in this disclosure
may be embodied as instructions on a computer-readable medium such
as random access memory (RAM), read-only memory (ROM), non-volatile
random access memory (NVRAM), electrically erasable programmable
read-only memory (EEPROM), FLASH memory, magnetic data storage
media, optical data storage media, or the like. The instructions
may be executed to support one or more aspects of the functionality
described in this disclosure.
* * * * *
References