U.S. patent application number 15/271160 was filed with the patent office on 2017-03-30 for user interfaces for heart test devices.
The applicant listed for this patent is Guangren Chen, Aaron Peterson. Invention is credited to Guangren Chen, Aaron Peterson.
Application Number | 20170086693 15/271160 |
Document ID | / |
Family ID | 58406071 |
Filed Date | 2017-03-30 |
United States Patent
Application |
20170086693 |
Kind Code |
A1 |
Peterson; Aaron ; et
al. |
March 30, 2017 |
User Interfaces for Heart Test Devices
Abstract
Heart condition and function can be visualized and/or quantified
using time-frequency maps derived from the time-frequency transform
of one or more electrocardiograms. The electrocardiograms,
time-frequency maps derived therefrom, and/or indices obtained by
analysis of the time-frequency maps and electrocardiograms may be
assembled into a user interface. Further embodiments are
described.
Inventors: |
Peterson; Aaron; (Frisco,
TX) ; Chen; Guangren; (Shanghai, CN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Peterson; Aaron
Chen; Guangren |
Frisco
Shanghai |
TX |
US
CN |
|
|
Family ID: |
58406071 |
Appl. No.: |
15/271160 |
Filed: |
September 20, 2016 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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62235309 |
Sep 30, 2015 |
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62276596 |
Jan 8, 2016 |
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62276639 |
Jan 8, 2016 |
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62321856 |
Apr 13, 2016 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61B 5/0456 20130101;
A61B 5/04012 20130101; A61B 5/7435 20130101; A61B 5/0006 20130101;
A61B 5/743 20130101; A61B 5/0452 20130101; A61B 5/044 20130101;
A61B 5/0408 20130101; A61B 5/726 20130101; A61B 5/04014 20130101;
A61B 5/0402 20130101; A61B 5/7253 20130101 |
International
Class: |
A61B 5/044 20060101
A61B005/044; A61B 5/04 20060101 A61B005/04; A61B 5/0408 20060101
A61B005/0408; A61B 5/0402 20060101 A61B005/0402 |
Claims
1. A method comprising: using one or more electrodes placed on a
patient, measuring one or more electrocardiograms associated with
one or more respective leads; using a processor, converting the one
or more electrocardiograms by time-frequency transform into one or
more corresponding two-dimensional time-frequency maps; and
generating a user interface displaying, for at least one of the one
or more electrocardiograms, at least a portion of the
electrocardiogram and, in temporal alignment therewith, a
temporally coextensive portion of the corresponding time-frequency
map.
2. The method of claim 1, further comprising: identifying, within
the one or more electrocardiograms, one or more points in time
associated with a T wave; determining at least one repolarization
index from values of the one or more time-frequency maps at the one
or more points in time associated with the T wave; and causing the
at least one repolarization index to be displayed in the user
interface.
3. The method of claim 2, wherein, for multiple leads, multiple
respective electrocardiograms are measured and transformed into
multiple corresponding time-frequency maps, and wherein the
generated user interface displays only a subset comprising fewer
than all of the multiple electrocardiograms and corresponding
time-frequency maps, the at least one repolarization index being
independent from a selection of electrocardiograms and
time-frequency maps for inclusion in the displayed subset.
4. The method of claim 2, wherein generating the user interface
comprises representing unsigned values of the one or more
time-frequency maps based on a color scale, and wherein the at
least one repolarization index is determined from signed values of
the one or more time-frequency maps at the one or more points in
time associated with the T wave.
5. The method of claim 2, further comprising determining a heart
condition based on the at least one repolarization index and
generating, for display within the user interface, an icon
indicative of the heart condition.
6. The method of claim 5, wherein the icon comprises a segmented
waveform symbol signifying, via a number of greyed-out segments
within the otherwise colored waveform symbol, a degree of
impairment of heart function.
7. The method of claim 1, wherein the displayed portions of the
electrocardiogram and the corresponding time-frequency map
encompass less than an entire measurement time of the
electrocardiogram, the method further comprising temporally
shifting, responsive to user input, the displayed portions of the
electrocardiogram and the corresponding time-frequency map.
8. The method of claim 7, wherein the displayed portions are
temporally shifted based on user input comprising a scrolling
action associated with at least one of a screen portion displaying
the electrocardiogram or a screen portion displaying the
corresponding time-frequency map.
9. The method of claim 8, wherein the scrolling action comprises a
swiping gesture performed within a screen portion displaying the
electrocardiogram or the corresponding time-frequency map and in a
direction substantially parallel to a time axis of the
electrocardiogram and the corresponding time-frequency map.
10. The method of claim 9, wherein the scrolling action is
performed on a touchscreen.
11. The method of claim 1, wherein the generated user interface
displays at least portions of multiple electrocardiograms and
corresponding time-frequency maps for multiple respective leads,
the portions of the electrocardiograms and time-frequency maps for
different ones of the leads being temporally coextensive and
temporally aligned with each other.
12. The method of claim 11, further comprising temporally shifting,
responsive to a scrolling action associated with one of the
electrocardiograms or the corresponding time-frequency map, the
displayed portions of all of the multiple electrocardiograms and
corresponding time-frequency maps.
13. The method of claim 1, wherein, for multiple leads, multiple
respective electrocardiograms are measured and transformed into
multiple corresponding time-frequency maps, and wherein the
generated user interface displays only a subset comprising fewer
than all of the multiple electrocardiograms and corresponding
time-frequency maps, the subset being selectable via one or more
user-input control elements included in the user interface.
14. The method of claim 13, wherein the user interface comprises
multiple screen portions, each facilitating, via an associated one
of the user-input control elements, user selection of one of the
measured electrocardiograms and the corresponding time-frequency
map for display in the screen portion.
15. The method of claim 14, wherein each of the user-input control
elements comprises a drop-down menu displaying, upon activation,
user-selectable symbols for all of the leads.
16. A heart test system comprising: an electrode interface
configured to receive one or more electrocardiogram signals via one
or more respective electrodes connectable to the electrode
interface; a display device; and a processing facility configured
to generate a user interface screen based at least in part on the
received one or more electrocardiogram signals and to cause display
of the user interface screen on the display device, wherein
generating and causing display of the user interface screen
comprises: generating, from the one or more electrocardiogram
signals, one or more electrocardiograms for one or more respective
leads; converting the one or more electrocardiograms by
time-frequency transform into one or more corresponding
two-dimensional time-frequency maps; generating a user interface
displaying, for at least one of the one or more electrocardiograms,
at least a portion of the electrocardiogram and, in temporal
alignment therewith, a temporally coextensive portion of the
corresponding time-frequency map.
17. The system of claim 16, wherein the processing facility is
further configured to: identify, within the one or more
electrocardiograms, one or more points in time associated with a T
wave; determine at least one repolarization index from values of
the one or more time-frequency maps at the one or more points in
time associated with the T wave; and cause the at least one
repolarization index to be displayed in the user interface.
18. The system of claim 17, wherein the processing facility is
configured to generate, from multiple electrocardiogram signals
received at the electrode interface, multiple electrocardiograms
for one or more respective leads, to convert the multiple
electrocardiograms into multiple corresponding time-frequency maps,
and to cause display, within the generated user interface, of only
a subset comprising fewer than all of the multiple
electrocardiograms and corresponding time-frequency maps, the at
least one repolarization index being independent from a selection
of electrocardiograms and time-frequency maps for inclusion in the
displayed subset.
19. The system of claim 17, wherein the processing facility is
configured to cause the one or more time-frequency maps to be
displayed by representing unsigned values of the one or more
time-frequency maps based on a color scale, and wherein the at
least one repolarization index is determined from signed values of
the one or more time-frequency maps at the one or more points in
time associated with the T wave.
20. The system of claim 17, wherein the processing facility is
further configured to determine a heart condition based on the at
least one repolarization index and generate, for display within the
user interface, an icon indicative of the heart condition.
21. The system of claim 20, wherein the icon comprises a segmented
waveform symbol signifying, via a number of greyed-out segments
within the otherwise colored waveform symbol, a degree of
impairment of heart function.
22. The system of claim 16, wherein the displayed portions of the
electrocardiogram and the corresponding time-frequency map
encompass less than an entire measurement time of the
electrocardiogram, the processing facility further configured to
temporally shift, responsive to user input, the displayed portions
of the electrocardiogram and the corresponding time-frequency
map.
23. The system of claim 22, wherein the display device comprises a
touch screen and the processing facility is configured to
temporally shift the displayed portions of the electrocardiogram
and the corresponding time-frequency map by processing a swiping
gesture performed on the touchscreen within a screen portion
displaying the electrocardiogram or the corresponding
time-frequency map and in a direction substantially parallel to a
time axis of the electrocardiogram and the corresponding
time-frequency map.
24. The system of claim 16, wherein the processing facility is
configured to cause display, within the generated user interface,
of at least portions of multiple electrocardiograms and
corresponding time-frequency maps for multiple respective leads,
the portions of the electrocardiograms and time-frequency maps for
different ones of the leads being temporally coextensive and
temporally aligned with each other.
25. The system of claim 24, wherein the display device comprises a
touch screen and the processing facility is configured to
temporally shift, responsive to a swiping gesture performed on the
touchscreen within a screen portion associated with one of the
electrocardiograms or the corresponding time-frequency map, the
displayed portions of all of the multiple electrocardiograms and
corresponding time-frequency maps.
26. The system of claim 16, wherein the electrode interface is
configured to receive multiple electrocardiogram signals via
multiple respective electrodes connectable to the electrode
interface, and the processing facility is configured to generate,
from the multiple electrocardiogram signals, multiple
electrocardiograms for multiple respective leads and convert them
into multiple respective time-frequency maps and to cause display
of only a subset comprising fewer than all of the multiple
electrocardiograms and corresponding time-frequency maps, the
subset being selectable via one or more user-input control elements
included in the user interface.
27. The system of claim 26, wherein the processing facility is
configured to cause display of multiple electrocardiograms and
corresponding time-frequency maps in multiple respective screen
portions each having an associated user-input control element that
facilitates user selection of one of the electrocardiograms and the
corresponding time-frequency map for display in the screen
portion.
28. The system of claim 27, wherein the user-input control elements
comprise a drop-down menu displaying, upon activation,
user-selectable symbols for all of the leads.
29. The system of claim 16, wherein the electrode interface, the
display device, and the processing facility are integrated into a
single heart test device.
30. One or more computer-readable media storing instructions for
processing one or more electrocardiograms associated with one or
more respective leads, the instructions, when executed by one or
more computer processors, causing the one or more processors to:
convert the one or more electrocardiograms by time-frequency
transform into one or more corresponding two-dimensional
time-frequency maps; and generate a user interface displaying, for
at least one of the one or more electrocardiograms, at least a
portion of the electrocardiogram and, in temporal alignment
therewith, a temporally coextensive portion of the corresponding
time-frequency map.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims priority to and the benefit of U.S.
Provisional Application No. 62/235,309, filed on Sep. 30, 2015,
U.S. Provisional Application No. 62/276,596, filed on Jan. 8, 2016,
U.S. Provisional Application No. 62/276,639, filed on Jan. 8, 2016,
and U.S. Provisional Application No. 62/321,856, filed on Apr. 13,
2016. The disclosures of all four provisional applications are
hereby incorporated herein by reference.
TECHNICAL FIELD
[0002] The present disclosure relates generally to heart testing,
and more particularly to systems, devices, and methods for
quantifying and/or visualizing heart condition.
BACKGROUND
[0003] Heart testing for coronary heart disease, myocardial
ischemia, and other abnormal heart conditions is routinely
performed using an electrocardiogram (ECG), which represents
electrical potentials reflecting the electrical activity of the
heart measured via electrodes placed on the patient's skin. The
heart's electrical system controls timing of the heartbeat by
sending an electrical signal through the cells of the heart. The
heart includes conducting cells for carrying the heart's electrical
signal, and muscle cells that contract the chambers of the heart as
triggered by the heart's electrical signal. The electrical signal
starts in a group of cells at the top of the heart called the
sinoatrial (SA) node. The signal then travels down through the
heart, conducting cell to conducting cell, triggering first the two
atria and then the two ventricles. Simplified, each heartbeat
occurs by the SA node sending out an electrical impulse. The
impulse travels through the upper heart chambers, called "atria",
electrically depolarizing the atria and causing them to contract.
The atrioventricular (AV) node of the heart, located on the
interatrial septum close to the tricuspid valve, sends an impulse
into the lower chambers of the heart, called "ventricles," via the
His-Purkinje system, causing depolarization and contraction of the
ventricles. Following the subsequent repolarization of the
ventricles, the SA node sends another signal to the atria to
contract, restarting the cycle. This pattern and variations therein
indicative of disease are detectable in an ECG, and allow medically
trained personnel to draw inferences about the heart's condition.
However, not every developing abnormality is immediately visible in
an ECG, and, consequently, many patients are misdiagnosed as
healthy. Furthermore, although ECGs are nowadays typically recorded
and displayed electronically, they often go little beyond the
printed ECG traces of the past in the type of information they
provide and the intuitiveness and convenience with which such
information is presented.
BRIEF DESCRIPTION OF THE DRAWINGS
[0004] FIG. 1 is a block diagram illustrating an example system for
quantifying and visualizing heart condition in accordance with
various embodiments.
[0005] FIG. 2 is an example ECG, illustrating various segments and
points in time used in accordance with various embodiments.
[0006] FIGS. 3A and 3B are graphs of an example ECG for a normal
heart and a scalogram resulting from its wavelet transform,
respectively, in accordance with one embodiment.
[0007] FIGS. 3C and 3D are graphs of an example ECG for an abnormal
heart and a scalogram resulting from its wavelet transform,
respectively, in accordance with one embodiment.
[0008] FIG. 4 is a flow chart of methods for quantifying and
visualizing heart condition, in accordance with various
embodiments.
[0009] FIG. 5 is a perspective view of an example heart test device
in accordance with various embodiments.
[0010] FIG. 6 is a user interface diagram for an example home
screen in accordance with various embodiments.
[0011] FIG. 7 is a user interface diagram showing an example report
screen in accordance with various embodiments.
[0012] FIGS. 8A-8C show the energy icon contained in the report
screen of FIG. 7 in three different states, corresponding to high
myocardial energy, moderate myocardial energy, and low myocardial
energy in accordance with various embodiments.
[0013] FIG. 9 is a user interface diagram showing a portion of the
example report screen of FIG. 7 in a different scrolling position,
in accordance with various embodiments.
[0014] FIG. 10 is a user interface diagram showing an example
report screen including a user-input control for lead selection in
accordance with various embodiments.
[0015] FIGS. 11A and 11B show a flow chart illustrating an
electrocardiography workflow in accordance with various
embodiments.
[0016] FIG. 12 is a block diagram of an example computer system as
may serve as processing facility in accordance with various
embodiments.
DESCRIPTION
[0017] Described herein, in various embodiments, are systems,
devices, and methods for enhancing the diagnostic capabilities and
utility of ECGs through advanced signal processing and through the
presentation of data in a meaningful, user-friendly way.
[0018] In accordance with various embodiments, ECGs--i.e.,
time-domain signals reflecting the electric potential of the heart
throughout one or more cardiac cycles--are computationally
converted, by a suitable time-frequency transform, into respective
two-dimensional time-frequency maps. In a "time-frequency map," as
the term is herein broadly understood, the signal value
(corresponding, e.g., to a measured electric potential) is provided
as a function of two independent variables: time, and a measure of
the spectral components of the signal such as, e.g., frequency (in
the narrower sense) or a scaling factor. For example, in some
embodiments, short-time Fourier transform is used to convert the
ECGs into spectrograms, where the signal value is a function of
time and frequency. In other embodiments, the ECGs are converted by
(continuous or discrete) wavelet transform into so-called
scalograms, where the signal value is a function of time and a
scaling factor. More generally, a filter bank may be used to
transform the ECG into a time-frequency representation. For ease of
reference, the dimension of the time-frequency map that corresponds
to the frequency or scaling factor (or any other measure of the
spectral components) is herein generally referred to as the
frequency dimension or simply frequency.
[0019] The time-frequency maps, by themselves or in conjunction
with the ECGs from which they are derived, may be displayed to a
physician (or other clinical personnel) for interpretation, and/or
analyzed automatically to derive quantitative metrics of heart
condition and function therefrom. By spreading out the spectral
components of the measured ECG signals, the time-frequency maps can
visualize information not discernible from the ECGs themselves,
which can help detect conditions traditionally not diagnosed based
on ECGs, such as, e.g., myocardial ischemia.
[0020] It has been found that the signal portion associated with
the T wave within the ECG, which represents the repolarization of
the ventricles, is a particularly suitable indicator of heart
condition. Accordingly, in various embodiments, repolarization
measures associated with one or more points in time (or ranges in
time) within the T wave are determined. More specifically, in some
embodiments, the T wave, and one or more relevant points in time
therein, are identified within an ECG, and the time-frequency map
derived from the ECG is then analyzed at the one or more points in
time to determine one or more extrema (i.e., maxima or minima) of
the signal value of the time-frequency map across frequency. (The
phrase "across frequency," in this context, means that the maximum
or minimum is determined for a fixed point in time from the signal
value of the time-frequency map as a (one-dimensional) function of
frequency only. By contrast, an extremum determined "across time
and frequency" is the maximum or minimum signal value within the
two-dimensional time-frequency map (or a two-dimensional portion
thereof, e.g., if the time dimension is limited to an interval).)
In certain embodiments, repolarization measures are determined for
the point in time where the T wave peaks (i.e., assumes its
maximum), and/or for "early" and/or "late" points in time within
the T wave, that is, for points in time preceding and/or following
the maximum of the T wave and being in the vicinity of that maximum
(e.g., points falling within a time interval defined by two points
bracketing the T wave maximum at which the T wave assumes half its
maximum value). In certain embodiments, the early and late times
are selected as close as possible to the peak while still being
distinguishable. A "repolarization peak measure (RPM)," a
"repolarization early measure (REM)," and a "repolarization late
measure (RLM)" are defined herein as the maximum or minimum signal
value of the time-frequency map at the time where the T wave peaks,
the early time, and the late time, respectively.
[0021] From one or more repolarization measures (e.g.,
corresponding to extrema across frequency at various points in time
associated with the T wave) determined for a patient, one or more
repolarization indices may be computed. For example, repolarization
measures (such as, e.g., REMs, RLMs, and/or RPMs) may be determined
from time-frequency maps computed from the ECGs of different leads
(signals acquired by different electrodes or combinations thereof),
and may be averaged across multiple leads, multiple cardiac cycles
within each time-frequency map, or both. Left and right ventricular
repolarization indices, indicative of the condition of the left or
right ventricles of the heart, may be derived from one or more
repolarization measures associated with leads associated with the
left and right ventricle, respectively, optionally in conjunction
with age- and/or gender-dependent adjustment factors and/or a
measured heart rate. The repolarization indices may be displayed or
otherwise communicated to a physician (or other clinically trained
person) to facilitate an assessment of the ventricles' condition,
or may be output to an automatic diagnosis algorithm. In some
embodiments, repolarization measures or repolarization indices are
compared against each other, or against a threshold, to assess
whether, and/or to which degree, heart function is impaired. For
example, an RLM exceeding an REM, a right ventricular
repolarization index exceeding a left ventricular repolarization
index, or an RLM or REM falling below a specified threshold may all
indicate an abnormality in heart function.
[0022] The overall signal level in ECGs, and consequently also the
time-frequency maps derived therefrom, can show significant
variations between measurements (e.g., taken at different times)
and between leads within a measurement that are unrelated to the
heart's condition and function and, thus, do usually not possess
clinical significance. Therefore, to render the data (including
ECGs, time-frequency maps, repolarization measures, and
repolarization indices) comparable across measurements, leads, or
even patients, the time-frequency map is normalized, in various
embodiments, prior to display and/or to the determination of the
repolarization measures. Normalization may be applied to the signed
time-frequency map as it results directly from time-frequency
transform, that is, a time-frequency map generally having both
positive and negative signal values, or to the unsigned
time-frequency map as it results by taking the absolute value of
the time-frequency transform. Further, the normalization may be
uniformly applied to the entire time-frequency map, or separately
to different portions thereof (e.g., portions corresponding to
individual heartbeats.) The normalization may be based on the
difference between the maximum and the minimum of the
time-frequency map (in its entirety) or a portion thereof (e.g., a
portion limited, in the time dimension, to a time interval
corresponding to an integer number of heartbeats, a single
heartbeat, or even only a segment of the ECG signal within a
heartbeat). For example, the time-frequency map may be shifted up
in signal value by the negative of its minimum value (such that the
minimum of the shifted map equals zero), and thereafter scaled
based on the (new) maximum value. Typically, the maximum of the
time-frequency transform corresponds to the R peak or the S peak
within the QRS complex (which are not always clearly identifiable
in each lead), but maxima falling outside the time interval
corresponding to the QRS complex are also possible. In various
embodiments, the portion of the time-frequency map across which a
maximum and minimum for normalization are identified is chosen to
encompass at least the RS segment.
[0023] In accordance with various embodiments, the ECGs,
time-frequency maps, and/or repolarization indices resulting from
heart testing are assembled into a user interface for display to,
e.g., a physician. The time-frequency maps may be shown as color
maps (which, if based on normalized signal values, may each span
the full color range from red to blue). Since, in general, not all
ECGs and associated time-frequency maps always fit simultaneously
within the display of the heart test device, the user interface may
provide user-input control elements that allow an operator to
select the leads for which ECGs and/or time-frequency maps are to
be displayed, and in which order. The user interface may further
enable the operator to scroll through all available leads and,
within the ECG and/or time-frequency map for a given lead, to
scroll along the time axis to different portions; in some
embodiments, such scrolling can be accomplished via a swiping
gesture on a touchscreen display. During scrolling along the time
axis, an ECG and its corresponding time-frequency map may be locked
so as to both display the same limited time range. In some
embodiments, the user interface further displays a Glasgow-analysis
summary (as known to those of ordinary skill in the art), and/or a
graphic icon generated based on the numerical repolarization
indices to provide an intuitive visual indicator of overall heart
condition. The icon may, for instance, be or include a segmented
waveform symbol that signifies, via a number of greyed-out segments
within an otherwise colored symbol, a degree of impairment of heart
function (e.g., whether the heart condition is normal, abnormal, or
suspect). The results of ECG testing may be displayed within a
report screen of a multiple-screen user interface configured to
guide clinical personnel through the electrocardiography process,
from patient selection and connection of the patient electrodes
through the performance of an electrocardiography test to the
presentation of the test results.
[0024] The foregoing will be more readily understood from the
following more detailed description, which references the
accompanying drawings.
[0025] FIG. 1 illustrates, in block-diagram form, various
functional components of an example system for quantifying and
visualization heart condition in accordance with various
embodiments. The system 100 includes one or more electrodes 102 for
acquiring ECG signals (e.g., 10 electrodes for a traditional
12-lead ECG), a processing facility 104 for processing the ECG
signals, e.g., to obtain time-frequency maps and repolarization
indices, and an electrode interface 106 connecting the electrodes
102 to the processing facility 104. The electrode interface 106
includes circuitry that outputs electrical signals suitable as
input to the processing facility 104, e.g., by digitally sampling
analog input signals. The system 100 further includes a display
device 108 for outputting the ECG test results (including, e.g.,
the ECGs, time-frequency maps, and/or repolarization indices), and
optionally other input/output devices 109, such as a keyboard and
mouse and/or a printer, for instance. The display device 108 may be
a touchscreen doubling as a user-input device. The processing
facility 104, electrode interface 106, display 108, and
input/output devices 109 may be implemented as a single,
stand-alone device implementing all computational functionality for
ECG signal processing and presentation. Alternatively, they may be
provided by the combination of multiple communicatively coupled
devices. For example, an ECG test device with limited functionality
for recording and/or processing ECG signals received from one or
more electrodes 102 via an electrode interface 106 of the device
may outsource certain computationally intense processing tasks to
other computers with which it is communicatively coupled via a
wired or wireless network. Thus, the functionality of the
processing facility 104 may be distributed between multiple
computational devices that communicate with each other. Whether
provided in a single device or distributed, the processing facility
104 may be implemented with dedicated, special-purpose circuitry
(such as, e.g., a digital signal processor (DSP),
field-programmable gate array (FPGA), analog circuitry, or other),
a suitably programmed general-purpose computer (including at least
one processor and associated memory), or a combination of both.
[0026] The processing facility 104 may include various functionally
distinct modules, such as an ECG-signal-processing module 110 that
prepares the (e.g., digitally sampled) electrical potentials for
display (e.g., by filtering, smoothing, scaling, etc.) and
analysis; a time-frequency transform module 112 that converts each
ECG signal into a two-dimensional time-frequency map (signed or
unsigned) and, optionally, normalizes the time-frequency map; an
index-builder module 114 that analyzes the ECGs and/or
time-frequency maps to determine repolarization measures and/or
repolarization indices (which may involve, e.g., identifying
delimiters between successive cardiac cycles, determining certain
features (such as the QRS complex, T wave, and other segments)
within the ECGs, selecting points in time within the T wave,
determining repolarization measures (such as, e.g., REMs, RLMs,
and/or RPMs) from the time-frequency maps, reading in any other
relevant parameters (such as gender- or age-based adjustment
factors, heart rate, etc.), and computing the ventricular indices
and/or any functions thereof); an analysis module 116 that derives
further metrics and/or determines heart condition from the
repolarization indices; and a user-interface 118 module that
generates graphic representations of the data provided by the other
modules and assembles them into a screen for display. The
ECG-signal-processing module 110 may be a conventional processing
module as used in commercially available heart monitors and/or as
is capable of straightforward implementation by one of ordinary
skill in the art. The time-frequency transform module 112,
index-builder module 114, analysis module 116, and user-interface
module 118 implement algorithms and provide functionality explained
in detail below, and can be readily implemented by one of ordinary
skill in the art given the benefit of the present disclosure.
[0027] As will be readily appreciated, the depicted modules reflect
merely one among several different possibilities for organizing the
overall computational functionality of the processing facility 104.
The modules may, of course, be further partitioned, combined, or
altered to distribute the functionality differently. The various
modules may be implemented as hardware modules, software modules
executed by a general-purpose processor, or a combination of both.
For example, it is conceivable to implement the time-frequency
transform module 112, which generally involves the same operations
for each incoming ECG signal, with special-purpose circuitry to
optimize performance, while implementing the index-builder module
114 and the analysis module 116 in software to provide flexibility
for adjusting parameters and algorithms, e.g., in response to new
medical data.
[0028] While the quantification of heart function in accordance
herewith is, in general, not limited to any particular number of
electrodes, the system 100 includes, in various embodiments, ten
electrodes 102 to facilitate obtaining a standard twelve-lead ECG,
as is routinely used in the medical arts. In accordance with the
standard configuration, four of the ten electrodes (conventionally
labeled LA, RA, LL, RL) are placed on the patient's left and right
arms and legs; two electrodes (labeled V1 and V2) are placed
between the fourth and fifth ribs on the left and right side of the
sternum; a further, single electrode (labeled V3) is placed between
V2 and V4 on the fourth intercostal space; one electrode (labeled
V4) is placed between the fifth and sixth ribs at the
mid-clavicular line (the imaginary reference line that extends down
from the middle of the clavicle), and, in line therewith, another
electrode (labeled V5) is positioned in the anterior axillary line
(the imaginary reference line running southward from the point
where the collarbone and arm meet), and the tenth electrode
(labeled V6) is placed on the same horizontal line as these two,
but oriented along the mid-axillary line (the imaginary reference
point straight down from the patient's armpit). The electric
potentials measured by electrodes V1 through V6 correspond to six
of the twelve standard leads; the remaining six leads correspond to
the following combinations of the signals measured with the
individual electrodes: I=LA-RA; II=LL-RA; III=LL-LA; aVR=RA-1/2
(LA+LL); aVL=LA-1/2 (RA+LL); and aVF=LL-1/2 (RA+LA).
[0029] FIG. 2 schematically shows an example ECG 200 for a single
cardiac cycle, illustrating the P wave 202, QRS complex 204 (which
includes the RS segment 206), and T wave 208. As depicted, the
electric potential usually reaches its maximum 210 at R during the
QRS complex 204. However, the polarity of the signal may be
inverted (such that the R peak has a negative value). Further, in
some ECG signals, the S peak has a greater absolute value than the
R peak. In fact, not every ECG unambiguously exhibits the features
shown in the (rather typical) example ECG 200. This uncertainty can
cause difficulty in attempts to normalize the signal based on a
discrete feature of the ECG such as, e.g., the R peak. To
circumvent this difficulty, various embodiments base normalization,
instead, on a signal maximum and minimum identified across a time
range, such as the time interval encompassing at least the RS
segment 206 (and thus including both the R and the S peak if they
are, in fact, clearly represented in the signal), irrespective of
the feature to which that maximum or minimum corresponds (if any).
FIG. 2 also illustrates certain points in time at which data is
evaluated in accordance with various embodiments, such as the time
212 at which the T wave 208 assumes its maximum, and example early
and late times 214, 216 bracketing the maximum of the T wave. In
general, the early and late times 214, 216 may be anywhere on the
rising edge and falling edge, respectively, of the T wave. In
various embodiments, they are selected within ranges between the T
wave maximum and points in time preceding and following the T wave
maximum, respectively, at which the T wave assumes some specified
fraction, e.g., half, of its maximum value.
[0030] In accordance herewith, the measured ECGs are transformed
into two-dimensional time-frequency maps by a suitable mathematical
transform, such as, for instance, wavelet transform. For a given
continuous ECG signal x(t), the continuous wavelet transform is
given by:
W ( a , b ) = 1 a .intg. - .infin. + .infin. .psi. ( t - b a ) _ x
( t ) t , ##EQU00001##
where .psi. is a selected wavelet, b corresponds to a shifted
position in time and a to a scaling factor, and W(a, b) is the
two-dimensional function of position in time and scale resulting
from the transform, also called wavelet coefficients. Similarly,
for a discretized ECG signal x(k) (where k is an integer), the
continuous wavelet transform is given by:
W ( a , b ) = 1 a k x ( k ) ( .intg. - .infin. ( k + 1 ) T .psi. (
t - b a ) _ t - .intg. - .infin. kT .psi. ( t - b a ) _ t ) ,
##EQU00002##
where T is the sampling period. The wavelet selected for processing
may be, for example, a Mexican hat wavelet, Morlet wavelet, Meyer
wavelet, Shannon wavelet, Spline wavelet, or other wavelet known to
those of ordinary skill in the art. Other well-known time-frequency
transforms that may be used alternatively to continuous or discrete
wavelet transform include, e.g., the short-term Fourier
transform.
[0031] The time-frequency maps (such as, e.g., scalograms)
generally include both positive and negative values. For an
intuitive interpretation of the signal value of the time-frequency
map as a measure of the electrical energy of the heart, however,
the sign is not relevant (since, in a measure of the energy, the
electrical potential is squared). Accordingly, in some embodiments,
the absolute value of the signal value (or the square of the signal
value) is taken at each time-frequency point, resulting in an
unsigned time-frequency map. The unsigned time-frequency map may be
advantageous, in particular, for display in a user interface (e.g.,
to a physician) since it avoids presenting information that is not
of immediate, intuitively discernible clinical significance and is
potentially distracting. On the other hand, since the signed
time-frequency map contains generally more information than the
unsigned time-frequency map, the computation of repolarization
measures and indices may (but need not) be based on the signed
map.
[0032] FIGS. 3A and 3B illustrate an example ECG for a normal heart
and an unsigned scalogram resulting from its wavelet transform
(followed by taking the absolute), respectively. In the scalogram,
the position b corresponding to time is along the abscissa and the
scale a (corresponding to frequency) along the ordinate, and the
signal value W is encoded by color or intensity (e.g., gray-scale
value). As can be seen, the various peaks of the normal ECG are
reflected in relatively high intensity in the scalogram, allowing
identification of the different ECG segments. For comparison, FIGS.
3C and 3D show an example ECG and associated scalogram,
respectively, for an abnormal heart. Here, features that are
prominent in the normal scalogram (e.g., the T wave) have rather
low intensity. While this lower intensity generally tracks the
lower values of the T wave in the ECG, it will be appreciated that
the scalogram may provide better visual clues. Accordingly, the
scalogram can aid a physician or other skilled clinician to assess
heart functioning.
[0033] To facilitate meaningful comparisons between time-frequency
maps derived from ECGs obtained simultaneously for different leads,
the time-frequency maps may be normalized. Normalization may
involve scaling and/or shifting signal values in the time-frequency
map to map the range of signal values in the map (or at least a
portion of the map, as explained below) to a specified numerical
range (hereinafter "target range"), e.g., 0 to 255 or -128 to +127
(as are convenient ranges for binary representations, and can, in
turn, be straightforwardly mapped onto color or gray-scale values
for display). Using a particular normalization and the associated
target range consistently not only across leads, but also across
measurements taken at different times and/or even for different
patients may also serve to improve comparability of data over time
and across the patient population, as it eliminates or at least
reduces overall signal-level variations, which are often not
attributable to different heart conditions, allowing physicians to
focus on the clinically relevant relative signal levels within a
time-frequency map.
[0034] The normalization may be based on a regional maximum and
minimum defined as the maximum and minimum of the time-frequency
map across frequency and across time within a selected interval,
and may then be applied to a second selected interval that may or
may not be the same as the first selected interval. The maximum and
minimum of the time-frequency map across frequency and across time
within that second selected interval are hereinafter called the
absolute maximum and minimum, and they may, but need not, coincide
with the regional maximum and minimum. The first selected interval
is typically, but not required to be, shorter than the second
selected interval. In some embodiments, the regional maximum and
minimum are determined across the entire time-frequency map,
corresponding to the entire measurement time of the ECG from which
it is derived, and the normalization is applied over that same
range (such that the first and second selected intervals are
equal). In other embodiments, the regional maximum and minimum are
identified within a portion of the time-frequency map that is
limited in its time dimension, e.g., to an integer number of
heartbeats (e.g., disregarding partial heartbeats) or only a single
heartbeat. A time-frequency map encompassing multiple heartbeats
may, for instance, be broken up into portions corresponding to
individual heartbeats, and each portion may be normalized
separately (potentially resulting in some discontinuity of the
signal values in the normalized time-frequency map); in this case,
first and second selected intervals are likewise equal to each
other. Normalization may even be based on a time interval
encompassing only part of a heartbeat, selected to likely (but not
certainly) include the absolute maximum and minimum. For instance,
in some embodiments, regional maximum and minimum are determined
within a portion of a time-frequency map that encompasses at least
the RS segment. Note, however, that it is possible for, e.g., the T
wave maximum to exceed the maximum in the QRS complex. In cases
where the absolute maximum and minimum of the time-frequency map
lie outside the portion of the map across which the regional
maximum and minimum are determined, the normalization will result
in signal values exceeding the target range. (Normalization may
also be applied in the time domain. In this case, the regional
minimum and maximum are across time over the selected time
interval.)
[0035] Normalization may be applied according to the following
equation:
n = ( d - d min ) * ( n max - n min ) ( d max - d min ) + n min ,
##EQU00003##
where [0036] n is the normalized data point; [0037] n.sub.min is
the normalized target-range minimum; [0038] n.sub.max is the
normalized target-range maximum; [0039] d is the data point to be
normalized; [0040] d.sub.min is the regional minimum; and [0041]
d.sub.max is the regional maximum. For example, to map onto the
target range from 0 to 255, n.sub.min is 0 and n.sub.max is 255; in
effect, this normalization shifts the time-frequency map to a
minimum equal to zero and thereafter scales the shifted map based
on its shifted regional maximum. More generally, the normalization
shifts the time-frequency map to a minimum equal to n.sub.min and
then scales the values of the shifted time-frequency map (taken
relative to the minimum value) by the ratio of the difference
between maximum and minimum of the target range to the difference
between the regional maximum and minimum.
[0042] Normalization can be applied to signed as well as unsigned
time-frequency maps. As will be appreciated, the result of the
normalization will vary depending on whether the underlying
time-frequency map is signed or unsigned. For example, when mapping
a signed time-frequency map with a positive R peak and a negative S
peak onto the target range from 0 to 255, several of the
frequencies at the point in time corresponding to the S peak will
map to or near zero. However, when the normalization is applied to
the absolute value of the otherwise same time-frequency map, some
frequencies at points in time between R and S will now map to or
near zero whereas several of the frequencies at the point in time
corresponding to the S peak will map onto a relatively larger
positive number within the target range.
[0043] The time-frequency maps (optionally following normalization)
may be displayed to a physician for evaluation. Alternatively or
additionally, they may be further analyzed, in accordance with
various embodiments, to determine various quantitative indicators
of heart condition and function. To that end, various measures of
the electric activity of the heart can be obtained, e.g., by
determining extrema (i.e., maximum and/or minimum values) across
frequency of the (normalized) time-frequency map (W or |W|) at
certain points (or ranges) in time corresponding to distinctive
features of the underlying ECGs, in particular, certain points (or
ranges) in time associated with the T wave. Measures associated
with the T wave are herein referred to as "repolarization measures"
and include, for example, the maximum value at an early time within
the T wave (REM), the maximum value at a late time within the T
wave (RLM), or the maximum value at the peak of the T wave (RPM).
Additional repolarization measures, e.g., including an integral
over a time interval within the T wave, may also be defined and
used to quantify heart condition.
[0044] From the repolarization measures determined in the
time-frequency map, one or more repolarization indices may be
derived, e.g., by averaging or based on information external to the
ECG or time-frequency map. For example, if the repolarization
measures are obtained based on ECGs covering multiple cardiac
cycles, the individually determined maxima may be averaged over
these cycles. Further, the various repolarization measures can
generally be derived separately from different time-frequency maps
obtained by transform of ECGs measured for different respective
leads, and repolarization measures of the same type (e.g., the
REMs) may be averaged across multiple leads. In particular,
ventricular repolarization indices may be derived by averaging only
across leads associated with the same (i.e., left or right)
ventricle. For example, a ventricular index early measure for the
right ventricle (VIEM_RV) may be calculated by (e.g.,
arithmetically) averaging over the REMs of leads V1 and V2, a
ventricular index late measure for the right ventricle (VILM_RV)
may be calculated by averaging over the RLMs of leads V1 and V2,
and a ventricular index peak measure for the right ventricle
(VIPM_RV) may be calculated by averaging over the RPMs of leads V1
and V2. Similarly, VIEM, VILM, and/or VIPM for the left ventricle
(VIEM_LV, VILM_LV, and VIPM_RV) may be calculated by averaging over
the REMs, RLMs, and RPMs, respectively, of leads V4, V5, and V6. In
certain embodiments, further indices are derived from the preceding
ones. For instance, a ventricular index average measure for the
right ventricle (VIAM_RV) may be calculated as the sum of VIEM_RV
and VILM_RV, divided by the heart rate (measured in beats per
minute). Similarly, a ventricular index average measure for the
left ventricle (VIAM_RV) may be calculated as the sum of VIEM_LV
and VILM_LV, divided by the heart rate. Further, in some
embodiments, an index for the heart as a whole is computed from
respective indices for the left and right ventricles, e.g., by
forming the ratio, difference, or some other function of left and
right ventricular indices.
[0045] Further, while the repolarization measures are generally
indicators of how well the heart functions, they can also be
affected by age and gender, independently of any abnormal heart
condition. To eliminate or at least reduce differences that do not
result from heart abnormalities, the repolarization measures may be
adjusted, when computing repolarization indices, with suitable age-
and/or gender-dependent factors. In one embodiment, the adjustment
distinguishes merely between male and female patients, using an
adjustment factor of 1 for males (i.e., keeping the measures as is)
and an adjustment factor smaller than one (e.g., 1/1.24) for
females. In some embodiments, further refinements are made to
distinguish between patients up to forty years old and patients
older than forty years. For example, for females older than forty
years, the adjustment factor may be decreased to 1/1.26. Other
age-based classifications and adjustment factors may be implemented
as well.
[0046] FIG. 4 is a flow chart summarizing methods 400 for
quantifying and visualizing heart condition in accordance with
various embodiments. The method 400 involves measuring one or more
ECGs associated with one or more respective leads (action 402),
using one or more electrodes placed on a patient. In some
embodiments, ten electrodes are used to obtain twelve leads. (The
phrase "measuring electrocardiograms" is intended to encompass both
the acquisition of electrocardiogram signals with the electrodes,
and the digitization and/or initial processing of these signals to
generate an electrocardiogram for each lead, which may include
combining multiple electrocardiogram signals to obtain an
electrocardiogram for a single lead, as described above.) In action
404, the ECG(s) are converted by time-frequency transform (e.g.,
wavelet transform) into one or more respective two-dimensional
time-frequency maps (e.g., scalograms). The time-frequency map(s)
may be used in the original signed form, or converted to unsigned
map(s) by taking the absolute value at each time-frequency point
(optional action 406), or both. Further, the time-frequency map(s)
may be normalized (action 408), as described above. In some
embodiments, for example, the time-frequency map is normalized
based on the maximum and minimum identified in the time-frequency
map across frequency and across a time interval encompassing at
least the RS segment (and, in some embodiments, encompassing a full
cardiac cycle (or heartbeat), multiple (an integer number of)
cardiac cycles, or the entirety of the measurement time).
[0047] To visualize the heart condition, a user interface
displaying the ECGs and/or corresponding time-frequency maps may be
generated (action 410). The signal values in the time-frequency
maps may be, e.g., color-coded or represented according to a gray
scale. To focus the user's (e.g., an interpreting physician's)
attention on the electrical energy of the heart, it may be
beneficial, as indicated above, to present unsigned (i.e.,
absolute-value) time-frequency maps. Due to spatial constraints,
the user interface may, at any given time, display only portions of
the ECGs and time-frequency maps corresponding to time intervals
smaller than the total measurement time. For example, out of data
for a twelve-second interval, the display may be limited to a
three-second subset. In addition, the number of ECGs and time
frequency maps displayed at any given time may be limited, e.g., to
three out of twelve ECGs and corresponding time-frequency maps. The
displayed selection of ECGs and time-frequency map and the
displayed time-range may depend on, and be adjusted based on, user
input (received at 412). For example, a drop-down menu displayed
next to each screen portion allocated to an ECG and time-frequency
map may facilitate selection of any of the available leads.
Further, the user may have the ability to scroll through the entire
measurement time, e.g., with a conventional scrollbar, or with a
swiping gesture performed, with a mouse-controlled cursor or on a
touchscreen, in a region displaying an ECG or time-frequency map.
In order to enable features within an ECG to be properly correlated
with features in the corresponding time-frequency map, the
displayed portions are temporally aligned (and, usually, temporally
coextensive), and the alignment is retained (or, in other words,
"locked in") as the user scrolls through the ECG or time-frequency
map. Further, if ECGs and time-frequency maps are displayed for
multiple leads, they may likewise be temporally aligned and
temporally coextensive, and locked-in in their alignment as the
user scrolls through any one of them.
[0048] To quantify heart condition, the time-frequency maps are
analyzed in conjunction with the respective ECGs. Specifically, in
action 414, one or more points in time associated with the T wave
(e.g., early and late times and/or the time where the T wave peaks)
are identified within an ECG. The corresponding time-frequency map
is then analyzed at these points in time to determine, separately
at each point in time (or within a small time interval surrounding
the respective points in time), a maximum and/or minimum across
frequency (action 416). The one or more extrema across frequency
determined in the time-frequency maps at one or more points in time
identified in respective ECGs constitute repolarization measures.
Based on these repolarization measures, one or more repolarization
indices can be determined in action 418. A repolarization index may
be based on (and in the simplest case be equal to) a single
repolarization measure or combine multiple repolarization measures
(e.g., by averaging repolarization measures over leads or cardiac
cycles). In addition, the repolarization index may include an
adjustment factor that is based on the age or gender of the
patient, or on some other characteristic of the patient or
circumstance of the measurement. The computed repolarization
indices may be output (in action 420) in various ways. For example,
they may be included in the user interface (e.g., along with the
ECGs and time-frequency maps) for display on-screen or in a
printable report, communicated to the user in some other manner, or
provided as input to another algorithm.
[0049] In some embodiments, the repolarization measures and/or
repolarization indices are automatically analyzed (action 422),
based on heuristics or empirical data, to obtain a qualitative
assessment of heart condition. For example, based on an expectation
that the early repolarization measure is greater than the late
repolarization measure, observation of a late repolarization
measure exceeding the early repolarization measure (for the same
ECG and time-frequency map) may be taken as a sign of abnormal or
impaired heart function, and communicated as such to the user.
Similarly, since the left ventricular repolarization index should
be greater than the right ventricular repolarization index for a
healthy heart, the reverse relationship (i.e., a right ventricular
repolarization index greater than the left repolarization index)
indicates an abnormality or impairment that may be communicated to
the user. Accordingly, comparisons between repolarization measures
and repolarization indices may be used to assess heart function.
Alternatively or additionally, repolarization measures and indices
(properly normalized or computed from normalized time-frequency
maps) may be compared against empirical thresholds. For example,
with a normalization of the time-frequency maps to a range from 0
to 255, an early or late repolarization measure for the left or
right ventricle that falls below a threshold in the range from
55-75 has been found to correlate strongly with some problem in
heart function. In some embodiments, one or more repolarization
indices are used to determine a myocardial energy category, e.g.,
distinguishing between high energy (corresponding to no or low
functional impairment), moderate energy (corresponding to moderate
functional impairment), and low energy (corresponding to high
functional impairment). Comparisons of repolarization measures
and/or repolarization indices against each other or against
specified thresholds in various combinations may also serve to
categorize heart function as normal, suspect, or abnormal.
[0050] Various modifications of the method 400 may be implemented.
For example, as noted above, ventricular indices may be computed
based on repolarization measures determined from values of the
time-frequency map at one or more points in time other than early
or late times, and/or over one or more ranges of time. Further, not
every action of the depicted method 400 need be implemented in
every embodiment. Accordingly, the depicted method 400 is to be
understood as one example embodiment only.
[0051] FIG. 5 shows an example heart test device 500 in perspective
view. The depicted device takes the form of a tablet computer 500
including a touchscreen display 502 as well as a control panel 504
with physical buttons (e.g., to power the tablet 500 on/off). In
some embodiments, as shown, the display 502 presents a multi-tab
user interface, explained in more detail below with respect to
FIGS. 6-10. Some of the tabs (shown along the right edge of the
display 502) may be duplicated by the physical buttons of the
control panel 504, allowing an operator to navigate between
different screens and associated device functions in different
ways. Electrodes for acquiring the ECG signals may be hooked up to
the tablet computer 500 via a suitable connector 506 (e.g., a DB15
connector). The tablet 500 contains a general-purpose processor and
volatile as well as non-volatile memory storing instructions for
implementing the functional processing modules 110, 112, 114, 116,
118. Of course, in various alternative embodiments, the heart test
device may take different form factors, such as that of a desktop
computer, laptop computer, or smartphone (to name just a few), each
with a suitable electrode interface, which may include custom
circuitry for converting the electrode signals into digital signals
suitable for further processing with software. Furthermore, an
electrocardiography system providing the functionality described
herein need not necessarily be implemented in a single device, but
can be provided by multiple devices used in combination, e.g., a
conventional ECG monitor connected to a general-purpose computer
running software to implement the processing functionality
described herein.
[0052] Turing now to the user interface, FIG. 6 depicts an example
home screen of the user interface as it may appear, e.g., when an
operator first turns on the ECG test device 500. The home screen
may, for example, provide links to reference materials such as a
quick-start guide and a more comprehensive user manual. In
accordance with one embodiment, as shown, the user interface
includes multiple tabs, corresponding to multiple respective
screens, that are visible in each screen (e.g., on the right hand
side), allowing easy navigation between the screens. The tabs may
be arranged in an order that corresponds to the natural workflow
through the electrocardiography process, described further below.
For example, in addition to the general tabs for the home screen
and a settings screen, the tabs may include, in this order, a
patient tab, a test tab, and a report tab.
[0053] FIG. 7 illustrates an example report screen in accordance
with various embodiments. As shown, the report screen may be
partitioned into multiple screen portions arranged in an intuitive
manner so as to allow the viewer to quickly locate the desired
information. At the top of the screen, patient information, such as
a unique patient identifier and the patient's name, as well as
patient-specific parameters affecting the interpretation of the
ECGs, such as age and gender, may be displayed, along with a record
identifier composed of, e.g., a date and time stamp for the test.
In a left panel, ECGs and time-frequency maps for one or more leads
may be displayed, e.g., in a vertical arrangement. The
time-frequency maps can visualize information not discernible from
the ECGs from which they are derived, e.g., by providing a picture
of the electrical energy of the heart during various stages within
the cardiac cycle, and can be useful in detecting conditions such
as myocardial ischemia, which are traditionally not diagnosed based
on ECGs. ECGs are included in the display because of their
familiarity to physicians and other medical practitioners and for
the purpose of identifying temporally defined features of the
signal, such as the QRS complex and T wave. In accordance with
various embodiments, the signal value of the time-frequency map
(e.g., the electrical potential or voltage that is plotted as a
function of time and frequency) is encoded in a color scale (or,
alternatively, as shown in the black-and-white drawings, in a grey
scale). While the signal value itself, as resulting from the
time-frequency (e.g., short-time Fourier or wavelet) transform
applied to the ECG, may be a signed value (generally resulting in
both positive and negative values across the map), the color-coded
depicted value may be unsigned, as obtained from a signed value by
computing the absolute value. Using unsigned signal values in the
color-coded maps serves to represent the energy level of the
time-dependent frequency content, independent of the phase of those
frequencies, thus allowing the energy of either positive or
negative phase to appear at the same point (along frequency) on the
time-frequency map.
[0054] As described above, the ECGs and time-frequency maps may be
analyzed, in accordance with various embodiments, to provide
quantitative indices indicative of heart health and/or a
qualitative assessment or categorization. The results of the
analysis may be presented, as shown in the right panel of FIG. 7,
in numerical, textual, and/or graphic form. For example, as shown,
the right panel may include an "energy icon" representing the
patient's overall heart health, a number of numerical indices
(e.g., repolarization indices as described above) providing a more
detailed picture underneath the icon, and a conventional
Glasglow-analysis textual summary underneath the numerical indices.
The Glasgow-analysis summary portion may display such metrics,
derived from the ECGs, as the patient's heart rate and durations of
certain ECG features (such as the QRS complex). In addition, it may
summarize the quality and reliability of the test, e.g., based on
signal-to-noise levels of various leads. Glasgow analysis is known
to those of ordinary skill in the art, and will not be further
elaborated upon herein.
[0055] FIGS. 8A-8C show the energy icon of FIG. 7 in isolation in
three different states, corresponding to high myocardial energy,
moderate myocardial energy, and low myocardial energy,
respectively. (These three states may be interpreted as normal,
suspect, and abnormal conditions, respectively.) In the depicted
embodiment, the energy icon is a segmented waveform symbol
including three segments 800, 802, 804, which are filled, for a
healthy patient (FIG. 8A), with a color gradient (shown, due to the
conversion to black-and-white drawings, with variations in the
grayscale value) mirroring the color scale of the time-frequency
maps. For a patient with moderately impaired heart function or
suspect heart condition (FIG. 7B), the first, left-most segment is
greyed-out (shown by a uniform grey filling as distinguished from
the previous variation). For a patient with strongly impaired or
abnormal heart function (FIG. 6C), both the left segment and the
middle segment are greyed out, symbolizing the much lower
myocardial energy. The energy icon, thus, provides a clinician with
an immediate visual clue as to the patient's heart health. As will
be readily appreciated, the energy icon is amenable to finer
gradation of the diagnostic assessment if modified to include more
than three segments.
[0056] For a large number of leads, e.g., for a full twelve-lead
ECG, it is generally impractical to display all twelve ECGs and
associated time-frequency maps at once on the display. Accordingly,
in various embodiments, the user is given the ability to scroll
vertically through the ECG (left) panel to view different ones of
the leads. For illustration, compare FIGS. 7 and 9, for example.
While, in FIG. 7, ECGs and time-frequency maps for leads I, II, and
III are shown, FIG. 9 illustrates the screen in a different
scrolling position where, instead, ECGs and time-frequency maps for
leads aVL and aVF can be seen.
[0057] Alternatively or additionally to being able to scroll
through all leads, the user may be given the opportunity to select
leads for display for each of the (sub-)portions of the left panel
and thereby specify the order in which the leads are displayed. In
various embodiments, the user-input controls for lead selection are
drop-down menus displayed, initially in their closed state,
adjacent the screen portions for respective ECGs and time-frequency
maps. Each drop-down menu lists, once activated and opened by the
operator, all twelve leads, facilitating user selection of any one
of the leads for display within the current screen portion; FIG. 10
illustrates an opened drop-down menu for the first displayed lead.
In some embodiments, once a new lead is selected, its position is
swapped with the lead that previously occupied the respective
screen portion. For example, if lead V1 is changed to lead V5 in
the drop-down menu, the vertical positions of the respective ECGs
and time-frequency maps will be swapped, and V1 will appear where
V5 was previously located.
[0058] As shown in the report screens depicted in FIGS. 7, 9, and
10, the ECGs may be displayed with the time axis extending
horizontally (as is customary). In accordance with various
embodiments, the corresponding time-frequency maps are likewise
oriented with their time axes in the horizontal direction, and are
temporally aligned with the ECGs, meaning that ECG and
corresponding time-frequency map both show a given point in time at
the same horizontal position. In addition to the temporal alignment
within a screen portion showing an ECG and time-frequency map
derived therefrom, the various screen portions displaying different
ECGs (and corresponding time-frequency maps) may likewise be
temporally aligned. Further, the left panel (and, indeed, the
screen) may not be wide enough to display the ECGs and
time-frequency maps in their entirety, covering the full
acquisition period. Instead, the ECGs and time-frequency maps may
be displayed partially, for a limited time range. The user
interface may facilitate, however, a horizontal scroll by the
operator through the ECG and/or time-frequency map to affect a
temporal shift of the limited time range being displayed. During
such a scroll, the ECG and corresponding time-frequency map may be
"locked" so as to maintain their temporal alignment. Analogously,
the other ECGs and time-frequency maps within the report screen may
be locked to the screen portion being scrolled through, and thus
move along with the scrolled through ECG/time-frequency map. A
scroll can be effected in various ways, such as by a traditional
scroll bar. In various embodiments, however, touchscreen capability
of the display of the heart monitor device is exploited to allow
scrolling via a swiping gesture performed on-screen in a direction
substantially horizontal (and thus parallel to the time axis of the
ECG), within a screen portion displaying the ECG and corresponding
time-frequency map. From the swiping gesture, a shifted limited
time range may be determined and applied to the shifting of the
displayed ECG/time-frequency map portions. (As will be readily
appreciated by one of ordinary skill in the art, the features of
temporal alignment and temporal locking described above are not
contingent upon the horizontal orientation of the time axis.
Rather, it is conceivable that ECGs and/or corresponding
time-frequency maps be displayed in a horizontal arrangement with
their time axes pointing downward, in which case the temporal
alignment would be vertical.)
[0059] FIGS. 11A and 11B provide a flowchart illustrating an
electrocardiography workflow 1100 supported by the depicted user
interface, in accordance with various embodiments. The medical
professional performing this workflow is, in a typical clinical
setting (but not necessarily), a nurse (rather than a physician).
Herein, the person operating the heart monitor device (e.g., to
perform the workflow depicted in FIGS. 11A and 11B, or to
subsequently view the results) is generically called the
"operator." In FIGS. 11A and 11B, actions of the operator are shown
on the right, and operations performed by the heart test device are
depicted on the left. Referring to FIG. 11A, the operator, being
presented with a multi-tab user interface (action 1102), generally
starts by selecting the patient tab (action 1104). On the patient
screen displayed as a result (action 1106), the operator can either
select an existing patient from a list (optionally in conjunction
with filtering based on operator-supplied search tokens), or create
a new patient, e.g., by pressing a "New" button displayed on the
screen and entering the relevant patient information (action 1108).
Once a patient has been selected, a pop-up message may briefly
appear on the patient screen to confirm the selection (action
1110).
[0060] The operator then navigates to the test screen (action
1112). If the patient has not already been prepped for the test
(e.g., electrodes have been attached to patient, patient cable has
been attached to heart monitor device and electrodes, etc.), the
operator can do so at this stage (action 1114). Once available, the
test screen displays real-time traces of the ECG signals (action
1116). The operator usually views the real-time ECG traces to
assess whether all the electrodes are connected and the ECG signals
are adequate to proceed with the test. Once the operator is
satisfied with the quality of the real-time traces, he can initiate
a test (action 1118) by pressing, e.g., a "Test" button provided on
the test screen. Upon activation, this button may be replaced by a
"Stop/Countdown Timer" button (action 1120) that displays the
remaining test duration while the test is running, and also
facilitates operator abortion of the test.
[0061] When the ECG test is complete, the user interface
automatically navigates the operator to the reports screen (action
1122). The reports screen may initially (e.g., during the first
15-20 seconds), while the indices and energy icon are being
computed, display merely the ECGs and corresponding time-frequency
maps as well as a Glasgow analysis summary for viewing by the
operator (action 1124). Optionally, a "Calculating . . . " or
similar text message may alert the operator that additional
information is forthcoming. An operator may simply wait for the
computation of the icon and indices to complete. Once the reports
screen is updated with the computed indices and icon (action 1126),
the operator may view the results (action 1128). The operator may
also be given the option to print or export the report (e.g., to an
external USB drive) (action 1130). If the operator chooses to print
the results (at 1128), a print-preview window may allow the
operator to navigate the possibly multiple pages of the report as
well as send the report to a network or physically attached
printer. Printing is useful to allow a physician (who is not the
operator) to view the test results offline before coming back into
the exam room to discuss the results with the patient.
[0062] The embodiments describe hereinabove relate to the
quantification and visualization of heart condition based on ECGs
in conjunction with time-frequency maps derived therefrom. Some of
the features described with reference to time-frequency maps may,
however, also apply to, and be advantageous in the context of, the
ECGs themselves. For example, for better comparability of the ECGs
across leads, measurements, and patients, the ECGs may be
normalized based on the absolute maximum and minimum of the ECG (in
its entirety) or a portion thereof. Values of the normalized ECGs
at certain points in time associated with the T wave may serve as
repolarization measures for quantification of heart condition.
[0063] Certain embodiments are described herein as including a
number of logic components or modules. Modules may constitute
either software modules (e.g., code embodied on a non-transitory
machine-readable medium or in a signal transmitted over a network)
or hardware-implemented modules. A hardware-implemented module is a
tangible unit capable of performing certain operations and may be
configured or arranged in a certain manner. In example embodiments,
one or more computer systems (e.g., a standalone, client or server
computer system) or one or more processors may be configured by
software (e.g., an application or application portion) as a
hardware-implemented module that operates to perform certain
operations as described herein.
[0064] In various embodiments, a hardware-implemented module may be
implemented mechanically or electronically. For example, a
hardware-implemented module may comprise dedicated circuitry or
logic that is permanently configured (e.g., as a special-purpose
processor, such as a field programmable gate array (FPGA) or an
application-specific integrated circuit (ASIC)) to perform certain
operations. A hardware-implemented module may also comprise
programmable logic or circuitry (e.g., as encompassed within a
general-purpose processor or other programmable processor) that is
temporarily configured by software to perform certain operations.
It will be appreciated that the decision to implement a
hardware-implemented module mechanically, in dedicated and
permanently configured circuitry, or in temporarily configured
circuitry (e.g., configured by software) may be driven by cost and
time considerations.
[0065] Accordingly, the term "hardware-implemented module" should
be understood to encompass a tangible entity, be that an entity
that is physically constructed, permanently configured (e.g.,
hardwired) or temporarily or transitorily configured (e.g.,
programmed) to operate in a certain manner and/or to perform
certain operations described herein. Considering embodiments in
which hardware-implemented modules are temporarily configured
(e.g., programmed), each of the hardware-implemented modules need
not be configured or instantiated at any one instance in time. For
example, where the hardware-implemented modules comprise a
general-purpose processor configured using software, the
general-purpose processor may be configured as respective different
hardware-implemented modules at different times. Software may
accordingly configure a processor, for example, to constitute a
particular hardware-implemented module at one instance of time and
to constitute a different hardware-implemented module at a
different instance of time.
[0066] Hardware-implemented modules can provide information to, and
receive information from, other hardware-implemented modules.
Accordingly, the described hardware-implemented modules may be
regarded as being communicatively coupled. Where multiple of such
hardware-implemented modules exist contemporaneously,
communications may be achieved through signal transmission (e.g.,
over appropriate circuits and buses) that connect the
hardware-implemented modules. In embodiments in which multiple
hardware-implemented modules are configured or instantiated at
different times, communications between such hardware-implemented
modules may be achieved, for example, through the storage and
retrieval of information in memory structures to which the multiple
hardware-implemented modules have access. For example, one
hardware-implemented module may perform an operation, and store the
output of that operation in a memory device to which it is
communicatively coupled. A further hardware-implemented module may
then, at a later time, access the memory device to retrieve and
process the stored output. Hardware-implemented modules may also
initiate communications with input or output devices, and can
operate on a resource (e.g., a collection of information).
[0067] The various operations of example methods described herein
may be performed, at least partially, by one or more processors
that are temporarily configured (e.g., by software) or permanently
configured to perform the relevant operations. Whether temporarily
or permanently configured, such processors may constitute
processor-implemented modules that operate to perform one or more
operations or functions. The modules referred to herein may, in
some example embodiments, comprise processor-implemented
modules.
[0068] Similarly, the methods described herein may be at least
partially processor-implemented. For example, at least some of the
operations of a method may be performed by one or processors or
processor-implemented modules. The performance of certain of the
operations may be distributed among the one or more processors, not
only residing within a single machine, but deployed across a number
of machines. In some example embodiments, the processor or
processors may be located in a single location (e.g., within a home
environment, an office environment or as a server farm), while in
other embodiments the processors may be distributed across a number
of locations.
[0069] The one or more processors may also operate to support
performance of the relevant operations in a "cloud computing"
environment or as a "software as a service" (SaaS). For example, at
least some of the operations may be performed by a group of
computers (as examples of machines including processors), these
operations being accessible via a network (e.g., the Internet) and
via one or more appropriate interfaces (e.g., Application Program
Interfaces (APIs).)
[0070] Example embodiments may be implemented in digital electronic
circuitry, or in computer hardware, firmware, software, or in
combinations of them. Example embodiments may be implemented using
a computer program product, e.g., a computer program tangibly
embodied in an information carrier, e.g., in a machine-readable
medium for execution by, or to control the operation of, data
processing apparatus, e.g., a programmable processor, a computer,
or multiple computers.
[0071] A computer program can be written in any form of programming
language, including compiled or interpreted languages, and it can
be deployed in any form, including as a stand-alone program or as a
module, subroutine, or other unit suitable for use in a computing
environment. A computer program can be deployed to be executed on
one computer or on multiple computers at one site or distributed
across multiple sites and interconnected by a communication
network.
[0072] In example embodiments, operations may be performed by one
or more programmable processors executing a computer program to
perform functions by operating on input data and generating output.
Method operations can also be performed by, and apparatus of
example embodiments may be implemented as, special purpose logic
circuitry, e.g., a field programmable gate array (FPGA) or an
application-specific integrated circuit (ASIC).
[0073] The computing system can include clients and servers. A
client and server are generally remote from each other and
typically interact through a communication network. The
relationship of client and server arises by virtue of computer
programs running on the respective computers and having a
client-server relationship to each other. In embodiments deploying
a programmable computing system, it will be appreciated that that
both hardware and software architectures require consideration.
Specifically, it will be appreciated that the choice of whether to
implement certain functionality in permanently configured hardware
(e.g., an ASIC), in temporarily configured hardware (e.g., a
combination of software and a programmable processor), or a
combination of permanently and temporarily configured hardware may
be a design choice.
[0074] FIG. 12 is a block diagram of a machine in the example form
of a computer system 1200 within which instructions for causing the
machine to perform any one or more of the methodologies discussed
herein may be executed. In alternative embodiments, the machine
operates as a standalone device or may be connected (e.g.,
networked) to other machines. In a networked deployment, the
machine may operate in the capacity of a server or a client machine
in server-client network environment, or as a peer machine in a
peer-to-peer (or distributed) network environment. While only a
single machine is illustrated, the term "machine" shall also be
taken to include any collection of machines that individually or
jointly execute a set (or multiple sets) of instructions to perform
any one or more of the methodologies discussed herein. The example
computer system 1200 includes one or more processors 1202 (e.g., a
central processing unit (CPU), a graphics processing unit (GPU) or
both), a main memory 1204 and a static memory 1206, which
communicate with each other via a bus 1208. The computer system
1200 may further include a video display unit 1210 (e.g., a liquid
crystal display (LCD) or a cathode ray tube (CRT)). The computer
system 1200 also includes an alphanumeric input device 1212 (e.g.,
a keyboard), a user interface (UI) navigation device 1214 (e.g., a
mouse), a disk drive unit 1216, a signal generation device 1218
(e.g., a speaker), a network interface device 1220, and a data
interface device 1228 (such as, e.g., an electrode interface
106).
[0075] The disk drive unit 1216 includes a machine-readable medium
1222 storing one or more sets of instructions and data structures
(e.g., software) 1224 embodying or utilized by any one or more of
the methodologies or functions described herein. The instructions
1224 may also reside, completely or at least partially, within the
main memory 1204 and/or within the processor 1202 during execution
thereof by the computer system 1200, the main memory 1204 and the
processor 1202 also constituting machine-readable media.
[0076] While the machine-readable medium 1222 is shown in an
example embodiment to be a single medium, the term
"machine-readable medium" may include a single medium or multiple
media (e.g., a centralized or distributed database, and/or
associated caches and servers) that store the one or more
instructions or data structures. The term "machine-readable medium"
shall also be taken to include any tangible medium that is capable
of storing, encoding, or carrying instructions for execution by the
machine and that cause the machine to perform any one or more of
the methodologies of the present invention, or that is capable of
storing, encoding or carrying data structures utilized by or
associated with such instructions. The term "machine-readable
medium" shall accordingly be taken to include, but not be limited
to, solid-state memories, and optical and magnetic media. Specific
examples of machine-readable media include non-volatile memory,
including by way of example semiconductor memory devices, e.g.,
Erasable Programmable Read-Only Memory (EPROM), Electrically
Erasable Programmable Read-Only Memory (EEPROM), and flash memory
devices; magnetic disks such as internal hard disks and removable
disks; magneto-optical disks; CD-ROM and DVD-ROM disks, or other
data-storage devices. Further, the term "machine-readable medium"
shall be taken to include a non-tangible signal or transmission
medium, including an electrical signal, a magnetic signal, an
electromagnetic signal, an acoustic signal and an optical
signal.
[0077] The following numbered examples are illustrative
embodiments:
[0078] 1. A method comprising: using one or more electrodes placed
on a patient, measuring one or more electrocardiograms associated
with one or more respective leads; converting the one or more
electrocardiograms by time-frequency transform into one or more
respective two-dimensional time-frequency maps; identifying, within
the one or more electrocardiograms, one or more points in time
associated with a T wave; determining, for at least one of the one
or more time-frequency maps, one or more repolarization measures
corresponding to extrema across frequency of the respective
time-frequency map at the one or more points in time associated
with the T wave; and outputting at least one repolarization index
based on the one or more repolarization measures.
[0079] 2. The method of example 1, further comprising normalizing
each of the one or more time-frequency maps based at least in part
on a difference between a maximum and a minimum identified in the
respective time-frequency map across time in an interval
encompassing an RS segment and across frequency, wherein the one or
more repolarization measures are determined from the normalized
time-frequency maps.
[0080] 3. The method of example 2, wherein normalizing the one or
more time-frequency maps comprises shifting each time-frequency map
to a minimum equal to zero and thereafter scaling the respective
time-frequency map based on the maximum.
[0081] 4. The method of example 1 or example 2, wherein the time
interval across which the maximum and minimum are identified in the
time-frequency map encompasses at least one heartbeat.
[0082] 5. The method of example 1 or example 2, wherein the time
interval across which the maximum and minimum are identified in the
time-frequency map encompasses a measurement time of the associated
electrocardiogram in its entirety.
[0083] 6. The method of example 1 or example 2, wherein the time
interval across which the maximum and minimum are identified in the
time-frequency map corresponds to an integer number of
heartbeats.
[0084] 7. The method of any one of examples 1-6, wherein the one or
more points in time associated with the T wave fall within a time
interval defined by points preceding and following a maximum of the
T wave at which the T wave assumes half of its maximum value.
[0085] 8. The method of example 7, wherein the one or more points
in time associated with the T wave comprise a first point in time
preceding the maximum of the T wave and a second point in time
following the maximum of the T wave.
[0086] 9. The method of example 8, wherein a first repolarization
measure corresponding to an extremum at the first point in time and
a second repolarization measure corresponding to an extremum at the
second point in time are determined, the method further comprising
comparing the first and second repolarization measures.
[0087] 10. The method of example 9, further comprising determining
a heart condition based on the comparison.
[0088] 11. The method of example 10, further comprising
communicating the heart condition to a user.
[0089] 12. The method of example 10 or example 11, wherein an
abnormal heart condition is determined based on the second
repolarization measure being greater than the first repolarization
measure.
[0090] 13. The method of any one of examples 1-12, wherein
electrocardiograms are measured and respective repolarization
measures are determined for at least one lead associated with a
left ventricle of the patient's heart and at least one lead
associated with a right ventricle of the patient's heart, and
wherein a left ventricular repolarization index based on the at
least one repolarization measure determined for the left ventricle
is compared with a right ventricular repolarization index based on
the at least one repolarization measure determined for the right
ventricle.
[0091] 14. The method of example 13, further comprising determining
a heart condition based on the comparison.
[0092] 15. The method of example 14, further comprising
communicating the heart condition to a user.
[0093] 16. The method of example 14 or example 15, wherein an
abnormal heart condition is determined based on the right
ventricular repolarization index being greater than the left
ventricular repolarization index.
[0094] 17. The method of any one of examples 13-16, wherein the
left ventricular repolarization index comprises an average over
multiple repolarization measures, corresponding to extrema at a
selected one of the points in time, determined based on
electrocardiograms measured for multiple respective leads
associated with the left ventricle, and the right ventricular
repolarization index is determined by averaging over multiple
repolarization measures, corresponding to extrema at the selected
point in time, determined based on electrocardiograms measured for
multiple respective leads associated with the right ventricle.
[0095] 18. The method of any one of examples 1-17, wherein the at
least one repolarization index comprises an average over two or
more repolarization measures.
[0096] 19. The method of example 18, wherein the average is taken
over two or more heart beats.
[0097] 20. The method of example 18 or example 19, wherein the
average is taken over two or more leads.
[0098] 21. The method of any one of examples 1-20, wherein the at
least one repolarization index comprises an adjustment factor that
is based on at least one of an age or a gender of the patient.
[0099] 22. The method of any one of examples 1-21, wherein the at
least one repolarization index is computed from the at least one
repolarization measure and a heart rate of the patient.
[0100] 23. The method of any one of examples 1-22, wherein the
time-frequency transform comprises a wavelet transform and the
time-frequency map comprises a scalogram.
[0101] 24. The method of example 23, wherein the time-frequency
transform comprises a continuous wavelet transform.
[0102] 25. The method of any one of examples 1-24, wherein the
time-frequency maps are absolute-value maps.
[0103] 26. The method of any one of examples 1-25, further
comprising determining a heart condition based on a comparison of
the at least one repolarization index against a threshold.
[0104] 27. The method of example 26, further comprising
communicating the heart condition to a user.
[0105] 28. The method of example 26 or example 27, wherein an
abnormal heart condition is determined based on the at least one
repolarization index being below the threshold.
[0106] 29. The method of any one of examples 1-28, wherein the
outputting comprises displaying the at least one repolarization
index in a user interface.
[0107] 30. A heart test system comprising: an electrode interface
configured to receive one or more electrocardiogram signals via one
or more respective electrodes connectable to the electrode
interface; and a processing facility communicatively coupled to the
electrode interface and configured to: generate, from the one or
more electrocardiogram signals, one or more electrocardiograms for
one or more respective leads; convert the one or more
electrocardiograms by time-frequency transform into one or more
respective two-dimensional time-frequency maps; identify, within
the one or more electrocardiograms, one or more points in time
associated with a T wave; determine, for at least one of the one or
more time-frequency maps, one or more repolarization measures
corresponding to extrema of the respective time-frequency map at
the one or more points in time associated with the T wave; and
output at least one repolarization index based on the one or more
repolarization measures.
[0108] 31. The system of example 30, wherein the electrode
interface and the processing facility are integrated into a single
heart test device.
[0109] 32. The system of example 30 or example 31, wherein the
processing facility is configured to implement the method of any
one of examples 2-29.
[0110] 33. One or more computer-readable media storing instructions
for processing one or more electrocardiograms associated with one
or more respective leads, the instructions, when executed by one or
more computer processors, causing the one or more computer
processors to: convert the one or more electrocardiograms by
time-frequency transform into one or more respective
two-dimensional time-frequency maps; identify, within the one or
more electrocardiograms, one or more points in time associated with
a T wave; determine, for at least one of the one or more
time-frequency maps, one or more repolarization measures
corresponding to extrema of the respective time-frequency map at
the one or more points in time associated with the T wave; and
output at least one repolarization index based on the one or more
repolarization measures.
[0111] 34. The one or more computer-readable media of example 33,
storing instructions which, when executed by the one or more
computer processors, cause the one or more computer processors to
carry out the method of any one of examples 2-29.
[0112] 35. A method comprising: using one or more electrodes placed
on a patient, measuring one or more electrocardiograms associated
with one or more respective leads; converting the one or more
electrocardiograms by time-frequency transform into one or more
corresponding two-dimensional time-frequency maps; and generating a
user interface displaying, for at least one of the one or more
electrocardiograms, at least a portion of the electrocardiogram
and, in temporal alignment therewith, a temporally coextensive
portion of the corresponding time-frequency map.
[0113] 36. The method of example 35, further comprising:
identifying, within the one or more electrocardiograms, one or more
points in time associated with a T wave; determining at least one
repolarization index from values of the one or more time-frequency
maps at the one or more points in time associated with the T wave;
and causing the at least one repolarization index to be displayed
in the user interface.
[0114] 37. The method of example 36, wherein, for multiple leads,
multiple respective electrocardiograms are measured and transformed
into multiple corresponding time-frequency maps, and wherein the
generated user interface displays only a subset comprising fewer
than all of the multiple electrocardiograms and corresponding
time-frequency maps, the at least one repolarization index being
independent from a selection of electrocardiograms and
time-frequency maps for inclusion in the displayed subset.
[0115] 38. The method of example 36 or 37, wherein generating the
user interface comprises representing unsigned values of the one or
more time-frequency maps based on a color scale, and wherein the at
least one repolarization index is determined from signed values of
the one or more time-frequency maps at the one or more points in
time associated with the T wave.
[0116] 39. The method of any one of examples 36-38, further
comprising determining a heart condition based on the at least one
repolarization index and generating, for display within the user
interface, an icon indicative of the heart condition.
[0117] 40. The method of example 39, wherein the icon comprises a
segmented waveform symbol signifying, via a number of greyed-out
segments within the otherwise colored waveform symbol, a degree of
impairment of heart function.
[0118] 41. The method of any one of examples 35-40, wherein the
displayed portions of the electrocardiogram and the corresponding
time-frequency map encompass less than an entire measurement time
of the electrocardiogram, the method further comprising temporally
shifting, responsive to user input, the displayed portions of the
electrocardiogram and the corresponding time-frequency map.
[0119] 42. The method of example 41, wherein the displayed portions
are temporally shifted based on user input comprising a scrolling
action associated with at least one of a screen portion displaying
the electrocardiogram or a screen portion displaying the
corresponding time-frequency map.
[0120] 43. The method of example 42, wherein the scrolling action
comprises a swiping gesture performed within a screen portion
displaying the electrocardiogram or the corresponding
time-frequency map and in a direction substantially parallel to a
time axis of the electrocardiogram and the corresponding
time-frequency map.
[0121] 44. The method of example 43, wherein the scrolling action
is performed on a touchscreen.
[0122] 45. The method of any one of examples 35-44, wherein the
generated user interface displays at least portions of multiple
electrocardiograms and corresponding time-frequency maps for
multiple respective leads, the portions of the electrocardiograms
and time-frequency maps for different ones of the leads being
temporally coextensive and temporally aligned with each other.
[0123] 46. The method of example 45, further comprising temporally
shifting, responsive to a scrolling action associated with one of
the electrocardiograms or the corresponding time-frequency map, the
displayed portions of all of the multiple electrocardiograms and
corresponding time-frequency maps.
[0124] 47. The method of any one of examples 35-46, wherein, for
multiple leads, multiple respective electrocardiograms are measured
and transformed into multiple corresponding time-frequency maps,
and wherein the generated user interface displays only a subset
comprising fewer than all of the multiple electrocardiograms and
corresponding time-frequency maps, the subset being selectable via
one or more user-input control elements included in the user
interface.
[0125] 48. The method of example 47, wherein the user interface
comprises multiple screen portions, each facilitating, via an
associated one of the user-input control elements, user selection
of one of the measured electrocardiograms and the corresponding
time-frequency map for display in the screen portion.
[0126] 49. The method of example 48, wherein each of the user-input
control elements comprises a drop-down menu displaying, upon
activation, user-selectable symbols for all of the leads.
[0127] 50. A heart test system comprising: an electrode interface
configured to receive one or more electrocardiogram signals via one
or more respective electrodes connectable to the electrode
interface; a display device; and a processing facility configured
to generate a user interface screen based at least in part on the
received one or more electrocardiogram signals and to cause display
of the user interface screen on the display device, wherein
generating and causing display of the user interface screen
comprises: generating, from the one or more electrocardiogram
signals, one or more electrocardiograms for one or more respective
leads; converting the one or more electrocardiograms by
time-frequency transform into one or more corresponding
two-dimensional time-frequency maps; generating a user interface
displaying, for at least one of the one or more electrocardiograms,
at least a portion of the electrocardiogram and, in temporal
alignment therewith, a temporally coextensive portion of the
corresponding time-frequency map.
[0128] 51. The system of example 50, wherein the electrode
interface, the display device, and the processing facility are
integrated into a single heart test device.
[0129] 52. The system of example 50 or example 51, wherein the
display device comprises a touchscreen.
[0130] 53. The system of any one of examples 50-52, wherein the
processing facility is configured to implement the method of any
one of examples 36-49.
[0131] 54. One or more computer-readable media storing instructions
for processing one or more electrocardiograms associated with one
or more respective leads, the instructions, when executed by one or
more computer processors, causing the one or more processors to:
convert the one or more electrocardiograms by time-frequency
transform into one or more corresponding two-dimensional
time-frequency maps; and generate a user interface displaying, for
at least one of the one or more electrocardiograms, at least a
portion of the electrocardiogram and, in temporal alignment
therewith, a temporally coextensive portion of the corresponding
time-frequency map.
[0132] 55. The one or more computer-readable media of example 54,
storing instructions which, when executed by the one or more
computer processors, cause the one or more processors to carry out
the method of any one of examples 35-49.
[0133] 56. A heart test device comprising: an electrode interface
configured to receive a plurality of electrocardiogram signals via
a plurality of respective electrodes connectable to the electrode
interface; a display device; and a processing facility comprising
circuitry configured to generate a user interface screen based at
least in part on the received electrocardiogram signals and to
cause display of the user interface screen on the display device,
wherein generating and causing display of the user interface screen
comprises: generating for display, based on the electrocardiogram
signals, a plurality of one-dimensional time-dependent
electrocardiograms for a plurality of respective leads; causing at
least partial display of a subset of the electrocardiograms,
corresponding to a subset of the leads, in multiple respective
screen portions of the user interface screen; causing display,
within each of the screen portions adjacent the electrocardiogram
at least partially displayed therein, of a user-input control
element facilitating user selection of any one of the plurality of
leads; and in response to user selection of one of the leads via
the user-input control elements, causing at least partial display,
within the corresponding screen portion, of the electrocardiogram
for the selected lead.
[0134] 57. The device of example 56, wherein the user-input control
element comprises a drop-down menu displaying, upon activation,
user-selectable symbols for all of the leads.
[0135] 58. The device of example 56 or example 57, wherein the at
least partially displayed electrocardiograms are temporally
aligned.
[0136] 59. The device of any of examples 56-58, wherein generating
and causing display of the user interface screen further comprises:
generating for display, from each of the one-dimensional
time-dependent electrocardiograms for the plurality of leads, a
corresponding two-dimensional time-frequency map; causing at least
partial display of a subset of the two-dimensional time-frequency
maps, corresponding to the subset of the leads, each time-frequency
map of the subset being displayed along with the corresponding
electrocardiograms within the corresponding screen portion; and, in
response to user selection of one of the leads via the user-input
control elements, causing at least partial display of the
time-frequency map for the selected lead in the corresponding
screen portion along with the corresponding electrocardiogram.
[0137] 60. A method comprising: measuring a plurality of
electrocardiogram signals using a plurality of respective
electrodes placed on a patient; using a processing facility to
generate a user interface screen based at least in part on the
received electrocardiogram signals and to cause display of the user
interface screen on a display device, wherein generating and
causing display of the user interface screen comprises: generating
for display, based on the electrocardiogram signals, a plurality of
one-dimensional time-dependent electrocardiograms for a plurality
of respective leads; causing at least partial display of a subset
of the electrocardiograms, corresponding to a subset of the leads,
in multiple respective screen portions of the user interface
screen; causing display, within each of the screen portions
adjacent the electrocardiogram displayed therein, of a user-input
control element facilitating user selection of any one of the
plurality of leads; and in response to user selection of one of the
leads via the user-input control elements, causing at least partial
display, within the corresponding screen portion, of the
electrocardiogram for the selected lead.
[0138] 61. A heart test device comprising: an electrode interface
configured to receive one or more electrocardiogram signals via one
or more respective electrodes connectable to the electrode
interface; a display device; and a processing facility comprising
circuitry configured to generate a user interface screen based at
least in part on the received one or more electrocardiogram signals
and to cause display of the user interface screen on the display
device, wherein generating and causing display of the user
interface screen comprises: generating, from the one or more
electrocardiogram signals, for each of one or more leads, a
one-dimensional time-dependent electrocardiogram; using a
time-frequency transform to compute, from each of the one or more
electrocardiograms, a corresponding two-dimensional time-frequency
map representing an unsigned signal value as a function of time and
frequency; causing, for at least one of the leads, display of
temporally aligned portions of the electrocardiogram and the
corresponding time-frequency map, the unsigned signal value of the
time-frequency map being color-coded.
[0139] 62. A method comprising: presenting, on a display of an
electronic heart monitor device, a multi-tab user interface
configured to guide an operator of the device through a
electrocardiography workflow, the multi-tab user interface
comprising at least a patient tab, a test tab, and a report tab; in
response to operator selection of the patient tab, presenting a
patient screen comprising one or more first user-input control
elements facilitating operator selection of a patient among a list
of existing patients and one or more second user-input control
elements facilitating operator entry of patient information for a
new patient; in response to operator selection of the test tab and
following connection of one or more electrodes to the heart monitor
device, presenting a test screen comprising one or more real-time
traces of one or more respective electrocardiogram signals measured
by the one or more connected electrodes and further presenting a
third user-input control element facilitating operator initiation
of an electrocardiogram test; upon operator selection of the third
user-input control element, causing acquisition of one or more
electrocardiogram signals throughout a specified test duration and
presenting, within the test screen, a fourth user-input control
element displaying a countdown timer based on the specified test
duration and facilitating operator abortion of the
electrocardiogram test; upon completion of the electrocardiogram
test, automatically presenting a reports screen associated with the
reports tab, the reports comprising report information including at
least one electrocardiogram computed based on the one or more
electrocardiogram signals and one or more fifth user-input control
elements facilitating operator initiation of at least one of
printing or exporting the report information.
[0140] Although the invention has been described with reference to
specific example embodiments, it will be evident that various
modifications and changes may be made to these embodiments without
departing from the broader spirit and scope of the invention.
Accordingly, the specification and drawings are to be regarded in
an illustrative rather than a restrictive sense.
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