U.S. patent number RE43,569 [Application Number 11/796,152] was granted by the patent office on 2012-08-07 for three dimensional vector cardiograph and method for detecting and monitoring ischemic events.
This patent grant is currently assigned to ECG-Tech Corp.. Invention is credited to Charles W. Olson.
United States Patent |
RE43,569 |
Olson |
August 7, 2012 |
Three dimensional vector cardiograph and method for detecting and
monitoring ischemic events
Abstract
A method of determining an ischemic event includes the steps of:
monitoring and storing an initial electrocardiogram vector signal
(x, y, z) of a known non-ischemic condition over the QRS, ST and T
wave intervals; calculating and storing a J-point of the vector
signal and a maximum magnitude of a signal level over the T wave
interval; monitoring a subsequent electrocardiogram vector signal
over the QRS, ST and T wave intervals; measuring and storing the
magnitude (Mag.) of the vector difference between a subsequent
vector signal and the initial vector signal; measuring and storing
the angle (Ang.) difference between a subsequent vector and the
initial vector at points; regressing a line from points about 25
milliseconds prior to the J point and about 60 milliseconds after
the J-point and determining the slope of the regression line and
the deviation of the angle difference of the regression line;
regressing a line from points about 100 milliseconds prior to the
maximum magnitude of the signal level over the T wave interval and
determining the slope of the regressing line and the deviation of
the angle difference of the regression line; and comparing the
slope and deviation of the lines from the J point and the T wave
interval to a set of known values to determine the presence of an
ischemic event.
Inventors: |
Olson; Charles W. (Huntington
Station, NY) |
Assignee: |
ECG-Tech Corp. (Huntington
Station, NY)
|
Family
ID: |
32474439 |
Appl.
No.: |
11/796,152 |
Filed: |
April 26, 2007 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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60431862 |
Dec 9, 2002 |
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Reissue of: |
10419427 |
Apr 21, 2003 |
6884218 |
Apr 26, 2005 |
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Current U.S.
Class: |
600/450; 600/512;
600/516; 600/517 |
Current CPC
Class: |
A61B
5/341 (20210101); A61B 5/366 (20210101); A61B
5/7239 (20130101) |
Current International
Class: |
A61B
8/06 (20060101); A61B 5/0402 (20060101); A61B
5/044 (20060101); A61B 5/0452 (20060101) |
Field of
Search: |
;600/509,512,516,517,450 |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
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0 383 697 |
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Aug 1990 |
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EP |
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0 383 697 |
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Aug 1990 |
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EP |
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0 674 873 |
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Oct 1995 |
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EP |
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0 674 873 |
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Oct 1995 |
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EP |
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Other References
PCT/US98/18557 International Search Report (Last three pages).
cited by other .
PCT/US98/18557 International Search Report. cited by other.
|
Primary Examiner: Heller; Tammie K
Attorney, Agent or Firm: Vodopia PC; John F.
Parent Case Text
CROSS REFERENCE TO RELATED APPLICATION
The present application claims the benefits of and priority to U.S.
Provisional Patent Application Ser. No. 60/431,862 filed on Dec. 9,
2002, the entire contents of which are incorporated herein by
reference.
Claims
What is claimed is:
.[.1. A method of determining an ischemic event, said method
comprising the steps of: monitoring and storing an initial
electrocardiogram vector signal (x1, y1, z1) of a known
non-ischemic condition over the QRS, ST and T wave intervals;
calculating and storing a J-point of the vector signal (x1, y1, z1)
and a maximum magnitude of a signal level over said T wave
interval; monitoring a subsequent electrocardiogram vector signal
(x2, y2, z2) over the QRS, ST and T wave intervals; measuring the
magnitude (Mag.) of the vector difference between a subsequent
vector signal (x2, y2, z2) and the initial vector signal (x1, y1,
z1); measuring the angle (Ang.) difference between a subsequent
vector (x2, y2, z2) and said initial vector signal (x1, y1, z1);
regressing a line from points about 25 milliseconds prior to the J
point and about 60 milliseconds after the J-point and determining
the slope of the regression line and the deviation of the angle
difference of said regression line; regressing a line from points
about 100 milliseconds prior to said maximum magnitude of the
signal level over said T wave interval and determining the slope of
the regressing line and the deviation of the angle difference of
said regression line; and comparing said slope and deviation of
said lines from said J point and said T wave interval to a set of
known values to determine the presence of an ischemic event..].
.[.2. A method according to claim 1 wherein the step of measuring
and storing the magnitude (Mag.) of the vector difference includes
the steps of: accessing the stored initial electrocardiogram vector
signal (x1, y1, z1) of a known non-ischemic condition over the QRS,
ST and T wave intervals; measuring said subsequent
electrocardiogram vector signal (x2, y2, z2) over the QRS, ST and T
wave intervals; calculating the change (.DELTA.) in the vector
signal over the QRS, ST and T wave intervals by the following
formula: .DELTA.x=x2-x1 .DELTA.y=y2-y1 .DELTA.z=z2-z1; and
calculating the magnitude of the vector difference (Mag.sub.vd)
over the QRS, ST and T wave intervals by the following formula:
Mag.sub.vd= (.DELTA.x.sup.2+.DELTA.y.sup.2+.DELTA.z.sup.2).].
.[.3. A method according to claim 1 wherein the step of measuring
and storing the angle of the vector difference (Ang.) includes the
steps of: accessing the stored initial electrocardiogram vector
signal (x, y, z) of a known non-ischemic condition over the QRS, ST
and T wave intervals; measuring said subsequent electrocardiogram
vector signal (x, y, z) over the QRS, ST and T wave intervals;
calculating the change (.DELTA.) in the vector signal over the QRS,
ST and T wave intervals by the following formula: .DELTA.x=x2-x1
.DELTA.y=y2-y1 .DELTA.z=z2-z1, calculating an Azimuth angle (Az.
Ang.) of said angle vector difference over the QRS, ST and T wave
intervals by the following formula: Az. Ang.=arc tan
(.DELTA.z/.DELTA.x); and calculating an Elevation angle (El. Ang.)
of said angle vector difference over the QRS, ST and T wave
intervals by the following formula: El. Ang.=arc tan(.DELTA.y/
(.DELTA.x.sup.2+.DELTA.z.sup.2))..].
.[.4. A method according to claim 1 wherein the step of calculating
said J point includes the steps of: calculating the magnitude of
the initial vector signal (Mag.sub.vs) over the QRS, ST and T wave
intervals by the following formula: Mag.sub.vs=
(x.sup.2+y.sup.2+z.sup.2); filtering said magnitude of the vector
signal (Mag.sub.vs) over the QRS, ST and T wave intervals through a
low pass filter to establish a smooth vector signal (VS.sub.sm) and
a maximum value and time of the QRS interval (QRS.sub.max and
QRS.sub.maxtime); differentiating said smooth vector signal
(VS.sub.sm) from said magnitude of the vector signal (Mag.sub.vs)
over the QRS, ST and T wave intervals and establishing a derivative
vector signal (dVS.sub.sm); calculating a set of initial parameters
from the QRS interval including: the magnitude of the maximum QRS
signal (QRS.sub.max1); the maximum of the QRS time interval
(QRS.sub.maxtime); and the end point of the QRS signal
(QRS.sub.EndInit); calculating a set of initial parameters from the
T wave interval including: the magnitude of the maximum T wave
signal (Twave.sub.max); and the maximum of the T wave time interval
(Twave.sub.maxtime); and calculating an initial estimate of the end
of the QRS interval (QRS.sub.EndInit); fitting the vector signal
along a cubic polynomial curve; calculating the change in the
derived vector signal (dVS.sub.sm) over a prescribed time period to
establish a smooth test interval (S.sub.Test); fitting a first
order polynomial curve to the initial vector signal (Mag.sub.vs)
starting at the end of the QRS interval (QRS_EndInit) to a point
which is equal to the end of the QRS interval (QRS_EndInit) plus
the smooth test interval (S.sub.Test); and calculating the
intersection of the cubic polynomial curve and the first order
polynomial curve and selecting a point of intersection that is
furthest from the time of the maximum QRS value (QRS.sub.maxtime)
to establish the J point..].
.[.5. A method according to claim 1 wherein after said step of
monitoring and storing an initial electrocardiogram vector signal
(x, y, z) of a known non-ischemic condition over the QRS, ST and T
wave intervals, the method includes the step of estimating a
magnitude and angle of said ST interval..].
.Iadd.6. A method of determining and displaying the presence of an
ischemic event implemented in a processor of a medical device, said
method comprising the steps of: monitoring and storing in said
processor an initial electrocardiogram vector signal (x1, y1, z1),
comprising a first sequence of samples, of a known non-ischemic
condition over the QRS, ST, and T wave intervals; calculating and
storing in said processor a magnitude (Mag.) and angle (Ang.) for
each sample of the first sequence of samples of the initial vector
signal (x1, y1, z1) including a J-point and a maximum magnitude
over each of the QRS, ST and T wave intervals; monitoring a
subsequent electrocardiogram vector signal (x2, y2, z2), comprising
a second sequence of samples including a J-point, and calculating a
magnitude (Mag.) and angle (Ang.) for each sample of the second
sequence of samples over the QRS, ST and T wave intervals; shifting
the first sequence of samples or the second sequence of samples,
where necessary, in order to substantially align the initial vector
signal (x1, y1, z1) and the subsequent vector signal (x2, y2, z2)
in time; calculating a difference vector (Vd) as a difference in
magnitude (Mag.) and a difference in angle (Ang.) between each
sequenced sample of the first sequence of samples and each
corresponding sequenced sample of the second sequence of samples
over the QRS, ST, and T wave intervals; regressing a line (A1) and
a line (E1) from scalar representatives of an Azimuth angle (Az.
Ang.) part and Elevation angle (El. Ang.) part of the sequenced
angle (Ang.) samples of the difference vector (Vd) from about 25
milliseconds prior to the J point to about 60 milliseconds after
the J-point; determining slopes of said regression line (A1) and
said regression line (E1); determining a standard deviation of an
angle difference between the samples comprising said regression
line (A1) and the corresponding azimuth angle (Az. An.) samples of
the difference vector (Vd), and a standard deviation of an angle
difference between the samples comprising said regression line (E1)
and the corresponding elevation angle (El. An.) samples of the
difference vector (Vd); and comparing said slopes and said standard
deviations of said angle differences of said regression line (A1)
and said regression line (E1) to a set of known slope values and
known standard deviation values to determine the presence of an
ischemic event..Iaddend.
.Iadd.7. A method according to claim 6 wherein the step of
calculating the difference vector (Vd), corresponding to the angle
(Ang.) difference includes the steps of: calculating changes
(.DELTA.) between each sample of the second sequence of samples and
each corresponding sample of the first sequence of samples over the
respective QRS, ST and T wave intervals by the following formulas:
.DELTA.x=x2-x1; .DELTA.y=y2-y1; .DELTA.z=z2-z1; and using the
.DELTA.x, .DELTA.y and .DELTA.z for each sample change, calculating
the Azimuth angle (Az. Ang.) part of said angle-(Ang.) difference
by the following formula: Az. Ang.=arctan(.DELTA.z/.DELTA.x); and
calculating the Elevation angle (El. Ang.) part of said
angle-(Ang.) difference by the following formula: El. Ang.=arctan
(.DELTA.y/((.DELTA.x.sup.2)+(.DELTA.z.sup.2)).sup.1/2), wherein
said angle (Ang.) difference for each sample of the difference
vector (Vd) comprises an AZ. Ang. and an El. Ang..Iaddend.
.Iadd.8. A method according to claim 6, further comprising, after
said step of monitoring and storing the first sequence of samples
and, said step of monitoring the second sequence of samples, a step
of utilizing the magnitude (Mag.) and angle (Ang.) at the J point
of the second sequence of samples as an estimated offset of the ST
interval..Iaddend.
.Iadd.9. A method according to claim 8, wherein the method further
comprises the step of: displaying, on a display in operative
communication with said processor, said J point of the second
sequence of samples..Iaddend.
.Iadd.10. A method according to claim 6, further comprising a step
of: displaying, on a display in operative communication with said
processor, said comparison of said slopes and said standard
deviations to visually communicate said determination of said
presence of said ischemic event..Iaddend.
.Iadd.11. A method according to claim 6, further comprising steps
of: regressing a line (A2) and a line (E2) from scalar
representations of Azimuth angle (Az. Ang.) and Elevation angle
(El. An.) parts of the sequenced angle (Ang.) samples of the
difference vectors (Vd), from about 100 milliseconds prior to said
maximum magnitude of the signal level over said T wave interval;
determining slopes of said regression line (A2) and said regression
line (E2); determining a standard deviation of an angle difference
between samples comprising said regression line (A2) and the
corresponding azimuth angle (Az. An.) samples of the difference
vector (Vd), and a standard deviation of an angle difference
between the samples comprising said regression line (E2) and the
corresponding elevation angle (El. An.) samples of the difference
vector (Vd); and comparing said slopes and said standard deviations
of said angle differences of said regression line (A2) and said
regression line (E2) to a set of known slope values and known
standard deviation values to determine the presence of an ischemic
event..Iaddend.
.Iadd.12. A method according to claim 6, wherein the initial
electrocardiogram vector signal (x1, y1, z1) is (0, 0,
0)..Iaddend.
.Iadd.13. A method for measuring and displaying a J-point of an
electrocardiogram signal implemented in a processor of a medical
device, the method comprising the steps of: monitoring and storing
an electrocardiogram vector signal (x, y, z) comprising a sequence
of samples over QRS, ST and T wave intervals of the
electrocardiogram signal; calculating and storing a corresponding
sequence of magnitudes (Mag.sub.vs), where each magnitude
(Mag.sub.vs) corresponds respectively to each of the sequence of
samples, a J-point and a maximum magnitude of a signal level of the
electrocardiogram vector signal (x, y, z) over the QRS, ST and T
wave intervals; filtering said sequence of magnitudes (Mag.sub.vs)
through a low pass filter to establish a smooth signal (VS.sub.sm),
a maximum value of the smooth signal (VS.sub.sm) in the QRS
interval (QRSVS.sub.max) and a time of occurrence of the maximum
value of the smooth signal (VS.sub.sm) in the QRS interval
(QRSVS.sub.maxtime); differentiating with respect to time the
smooth signal (VS.sub.sm) to establish a derivative of the smooth
signal (dVS.sub.sm) with respect to time; calculating a set of
initial parameters from the smooth signal (VS.sub.sm) in the QRS
interval including: an initial estimated time of the start of the
QRS interval (QRS.sub.startInit) by finding the time before the
time of occurrence of the maximum value of the smooth signal
(Vs.sub.sm) in the QRS interval (QRSVS.sub.maxtime) that the
derivative of the smooth signal (dVS.sub.sm) changes polarity from
negative to positive; and an initial estimated time of occurrence
of the end point of the QRS interval (QRS.sub.endInit) by finding
the time of occurrence after the time of occurrence of the maximum
smooth signal (VS.sub.sm) in the QRS interval (QRSVS.sub.maxtime)
at which the derivative of the smooth signal (dVS.sub.sm) changes
polarity from negative to positive; and displaying, on a display in
operative communication with said processor, said initial estimated
time of the end point of the QRS interval
(QRS.sub.endInit)..Iaddend.
.Iadd.14. A method according to claim 13, further comprising the
steps of: fitting said sequence of magnitudes (Mag.sub.vs) along a
cubic polynomial curve extending from a sample midway between the
time of occurrence of the maximum value of the smooth signal in the
QRS interval (QRSVS.sub.maxtime) and the initial estimated time of
occurrence of the end point of the QRS interval (QRS.sub.endInit),
to a sample at the initial estimated time of occurrence of the end
point of the QRS interval (QRS.sub.endInit); calculating a change
in the derivative of the smooth signal (dVS.sub.sm) for a period
extending in a range of 50 to 100 ms, beyond the initial estimated
time of occurrence of the end point of the QRS interval
(QRS.sub.endInit) to establish a smooth test interval (S.sub.Test);
fitting a first order polynomial curve to said sequence of
magnitudes (Mag.sub.vs) starting at the initial estimated time of
occurrence of the end point of the QRS interval (QRSendinit) and an
end point of the smooth test interval (S.sub.Test); calculating
points of intersection of the cubic polynomial curve and the first
order polynomial curve; and selecting a point of intersection that
is furthest in time from the time of occurrence of the maximum
value of the smooth signal (VS.sub.sm) in the QRS interval
(QRSVS.sub.maxtime), which intersection point is a true end of the
QRS interval (QRS.sub.trueend), and identifying the true end as the
J point..Iaddend.
.Iadd.15. A method according to claim 14, further comprising the
step of displaying, on a display in operative communication with
said processor, said J point..Iaddend.
.Iadd.16. A method for determining and displaying from an
electrocardiogram signal at least one of a beginning and an end of
the P-wave interval, a duration of the P-wave interval, a start of
the QRS interval, an end of the T-wave interval, a QT interval, a
PR interval, and a duration of the QRS interval, the method
implemented in a processor within a medical device and comprising
the steps of: monitoring and storing an electrocardiogram vector
signal (x, y, z), comprising a sequence of samples, from the
electrocardiogram signal over an entire heart beat cycle including
the P-wave, QRS, and T-wave intervals; calculating a magnitude for
each of the samples of the electrocardiogram vector signal (x, y,
z) over the P-wave, QRS and T-wave intervals, to realize a
corresponding sequence of magnitude values comprising a magnitude
signal (Mag), by the following formula:
Mag=((x.sup.2)+(y.sup.2)+(z.sup.2)).sup.1/2 filtering the
calculated magnitude signal (Mag) over the P-wave, QRS, and T-wave
intervals to establish: a smooth signal (VS.sub.sm); a time of
occurrence of a maximum value of the smooth signal (VS.sub.sm)
during the P-wave interval (Pwmaxtime); a magnitude of the maximum
value of the smooth signal (VS.sub.sm) during the P-wave interval
(Pwmax); a time of occurrence of the maximum value of the smooth
signal (VS.sub.sm) during the QRS interval (QRSVSmaxtime); a
magnitude of the maximum value of the smooth signal (VS.sub.sm)
during the QRS interval (QRSVSmaxtime); a time of occurrence of the
maximum value of the smooth signal (VS.sub.sm) during the T-wave
interval (Twmax); and a magnitude of the maximum value of the
smooth signal (VS.sub.sm) during the T-wave interval (Twmaxtime);
establishing a derivative vector signal (dVS.sub.sm) with respect
to time of the smooth signal (VS.sub.sm); calculating from the
smooth signal (VS.sub.sm) over the P-wave interval an initial
estimated time of the start of the P-wave interval (PwStInit) at a
point where the derivative signal (dVS.sub.sm) changes from
negative to positive, before the time of occurrence of the maximum
value of the smooth signal (VS.sub.sm) during the P-wave interval
(Pwmaxtime) and the initial estimated time of the end point of the
P-wave interval (PwEndInit) where the derivative signal changes
from negative to positive after the time of occurrence of the
maximum value of the smooth signal (VS.sub.sm) during the P-wave
interval (Pwmaxtime); and displaying, on a display in operative
communication with said processor, the magnitude of the maximum
value of the smooth signal (VS.sub.sm) during the P-wave interval
(Pwmax), the time of occurrence of the maximum value of the smooth
signal (VS.sub.sm) during the P-wave interval (Pwmaxtime), the
initial estimated time of the start of the P-wave interval
(PwTimeStInit), and the initial estimated time of the end of the
P-wave interval (PwTimeEndInit)..Iaddend.
.Iadd.17. A method according to claim 16, further comprising the
steps of: calculating from the smooth signal (VS.sub.sm) over the
QRS interval an initial estimated time of the start of the QRS
interval (QRSStInit) at a point where the derivative signal
(dVS.sub.sm) has a first zero value, before the time of occurrence
of the maximum value of the smooth vector signal (VS.sub.sm) of the
electrocardiogram vector signal (x, y, z) during the QRS interval
(QRSVSmaxtime)..Iaddend.
.Iadd.18. A method according to claim 17, further comprising the
steps of: calculating from the smooth signal (V.sub.sm) over the
T-wave interval an initial estimated time of occurrence of the end
point of the T-wave interval (TwTimeEndInit) at a point in time
where the derivative of the smooth signal (dVS.sub.sm) changes from
negative to positive after the time of occurrence of the maximum
smooth signal (VS.sub.sm) during the T-wave interval
(Twmaxtime)..Iaddend.
.Iadd.19. A method according to claim 18, further comprising the
steps: fitting a first cubic polynomial curve to the smooth signal
(VS.sub.sm), from the initial estimated time of the start of the
P-wave interval (PwaveTimeStInit) to the time of occurrence of the
maximum smooth signal (VS.sub.sm) during the P-wave interval
(Pwmaxtime); and finding a point (1) within the first cubic
polynomial curve displaying a magnitude equivalent to an average of
the signal magnitude (Mag.sub.vs) averaged over a region that
starts 20 ms before the initial estimated time of the start of the
P-wave interval (PwaveTimeStInit) and ends at the initial estimated
time of the start of the P-wave interval (PwaveTimeStInit), wherein
said point (1) comprises a refined estimate of the start of the
P-wave interval (PwStart)..Iaddend.
.Iadd.20. A method according to claim 19, further comprising the
steps: fitting a second cubic polynomial curve to the smooth signal
(VS.sub.sm), from the time of occurrence of the maximum smooth
signal (VS.sub.sm) during the P-wave interval (Pwmaxtime) to the
initial estimated time of the end of the P-wave interval
(PwaveTimeEndInit); and finding a point (2) within the second cubic
polynomial curve equal to a magnitude equivalent to an average of
the magnitude signal (Mag.sub.vs) averaged over a region that
begins at the initial estimated time of the end of the P-wave
interval (PwaveTimeEndInit) and ends at the initial start time of
the QRS interval (QRStime StartInit), wherein said point (2)
comprises a refined estimate of the time of occurrence of the end
of the P-wave interval (PwEnd)..Iaddend.
.Iadd.21. A method according to claim 20, further comprising the
steps: fitting a third cubic polynomial curve to the smooth signal
(VS.sub.sm), from the initial start time of the QRS interval
(QRStimeStartInit) to the time of occurrence of the maximum value
of the smooth signal (VS.sub.sm) during the QRS interval
(QRSVSmaxtime); and finding a point (3) within the third cubic
polynomial curve equal to a magnitude equivalent to an average of
the magnitude signal (Mag.sub.vs) averaged over a region that
starts from the initial estimated time of the end of the P-wave
interval (PwTimeEndInit) and extends to the initial estimated time
of the start of the QRS interval (QRSStInit), wherein said point
(3) comprises a refined estimate of the start time of the QRS
interval (QRSStart)..Iaddend.
.Iadd.22. A method according to claim 21, further comprising the
step of: calculating the PR interval, using the following formula:
PR interval=QRSStart-PwStart..Iaddend.
.Iadd.23. A method according to claim 21, further comprising the
step of: fitting a fourth cubic polynomial curve to a portion of
the smooth signal (VS.sub.sm) that extends from a point midway
between the time of occurrence of the maximum smooth signal
(VS.sub.sm) in the Twave interval (Twmaxtime) and the initial
estimated time of occurrence of the end point of the Twave interval
(TwTimeEndInit)..Iaddend.
.Iadd.24. A method according to claim 23, further comprising the
steps of: calculating a change in the derivative of the smooth
signal (dVS.sub.sm) over a prescribed time period after the initial
estimated time of occurrence of the end point of the T wave
interval (TwTimeEndInit) when the derivative of the smooth signal
(dVS.sub.sm) exhibits a substantially constant magnitude to
establish a post T wave smooth test interval (Twtime endInit+Post
Twsmoothtest); fitting a first order polynomial curve to a portion
of the smooth signal (VS.sub.sm) that starts at the initial
estimated time of occurrence of the end point of the T wave
interval (TwTimeEndInit) and extends through the initial estimated
time of occurrence of the end point of the T wave interval
(TwTimeEndInit) for about another 20 ms; calculating points of
intersection of the fourth cubic polynomial curve and the first
order polynomial curve; and selecting one of the points of
intersection that is furthest in time from the time occurrence of
the maximum smooth signal (VS.sub.sm) during the Twave interval
(Twavemaxtime), which said one of the points comprises the time of
occurrence of the end point of the T wave interval
(TwaveEnd)..Iaddend.
.Iadd.25. A method according to claim 24, further comprising the
step of displaying, on a display in operative communication with
said processor, said time of occurrence of the end point of the T
wave interval (TwaveEnd)..Iaddend.
Description
BACKGROUND
The present disclosure relates to a method for detecting and
monitoring electrical signals from the heart for analysis of heart
malfunctions. More particularly, the presently disclosed method
relates to a technique for distinguishing between ischemic
electrocardiograph (ECG) events and patient positional changes
during patient monitoring.
Multi-lead ECGs for diagnosing various heart maladies have been
used for many years. The most prevalent technique for analyzing and
diagnosing heart conditions involves a 12-lead system. The 12-Lead
system provides much redundant information in the frontal plane (X,
Y) and transverse plane (X, Z) of the ECG vector signal. It permits
only a rough visual estimate of the vector direction in theses two
planes. Other techniques such as two-dimensional (2-D) vector
cardiograms have proven in the past to be quite expensive and
cumbersome due to the relative cost and size of the equipment
needed to properly display the vector cardiograms, e.g., one
cathode ray tube (CRT) oscilloscope was needed for the display of
each bodily plane. Further, analysis of the 2-D vector cardiograms
typically required a high degree of technical skill and mental
agility in interrelating the three displays to formulate a good
picture of the 3-D vector. Rules were established on the basis of
individual 2-D diagrams and the 3-D vector effect was lost. As a
result, the 12-Lead system has become prevalent and widely
accepted.
However, in order to teach the 12-lead system, it has always been
important for doctors to have a rudimentary knowledge of the
relation of the ECG signal to the electrical activity of the heart.
This relation is briefly summarized below.
The heart pulse is initiated by the Sino-artial (S-A) node which is
generally located in the right atrium and, in a normal heart, acts
as the heart's chief pacemaker. The stimulation or depolarization
of the entire atria takes place after the occurrence of the S-A
node pulse. A graphical representation of the initial
depolarization of the atria on the electrocardiogram is represented
by a positive deflection on the ECG and is commonly called the
P-wave (See FIG. 12).
After an initial electrical pulse from the S-A node, depolarization
of the heart muscle spreads to the atrioventicular (A-V) node and
is then conducted to the "Bundle of His" (during which time it is
slowed down to allow for the atria to pump blood into the
ventricles) and thereafter to the "Bundle Branches". This is known
as the PR Segment. The P-R Interval represents the time of
transmission of the electrical signal from the initial S-A node
impulse to the ventricles.
Ventricle depolarization is known on an ECG by the QRS complex
which relates to the contraction or depolarization of the heart
muscles, in particular, the right ventricle and left ventricle.
This is the most studied cycle and is considered to be the most
important for the prediction of health and survivability of a
patient. It is initiated by the signal from the Bundle of His and
then the high speed Purkinje muscle fibers rapidly excite the
endocardium of the left ventricle and then the right ventricle.
Early experimental work showed the timing of this excitation and
the progress of the electrical wave through the right and left
ventricles of the heart, however, it was very difficult to
determine the net vector effect of this 3-D wave and its
relationship to the overall movement of the cardiac muscle. As a
result, most textbooks and physicians have adopted a simplified
two-dimensional approach to analyzing this problem.
On the graph shown in FIG. 12, ventricular depolarization is
clearly discernible. The most easily recognizable deflection
(positive deflection--upward movement above the base line on the
ECG) of the QRS complex is termed the R-wave. Just prior to this
deflection is the Q-wave which is typically represented by an
inverted signal deflection (negative deflection--downward movement
below the base line on the ECG). The negative deflection after the
R-wave is termed the S-wave which is the terminal part of the QRS
complex. (See FIG. 12).
Repolarization occurs after the termination of the S-wave and
starts with another positive deflection know as the T-wave. The
time frame for the initiation of repolarization is termed the S-T
segment and is usually represented by an isoelectric signal, i.e.,
neither positive or negative deflection. This S-T segment is a most
important indicator of the health of the ventricular
myocardium.
In order to show these electrical signals as they activate and
stimulate the heart muscle, a system had to be developed to record
the signals as they transverse the cardiac muscle. Einthoven found
that by placing electrodes at various positions on the body and
completing the circuit between the heart muscle and the
electrocardiogram, it was possible to view the electrical activity
between two electrodes of the heart. Each view derived from the
varying placement of the electrodes was known as a "Lead". For most
purposes, a typical ECG screening involves using a 12-Lead system
in which the leads are arranged at various points of the body,
e.g., outer extremities, and the signals are recorded across each
"Lead". A physician is trained to analyze and interpret the output
from these Leads and make a diagnosis. In order to help a physician
make an accurate diagnosis, various formulas and methods have been
developed which translate the output of the 12-Lead system into
workable solutions, e.g., Einthoven's Law and 2-D Vector
Cardiography.
In order to better explain the novel aspects and unique benefits of
the present invention, a brief explanation of vector cardiographic
analysis and the numerous steps and processes a physician typically
undergoes in order to offer a somewhat accurate diagnosis is
relevant.
Vector Cardiography uses a vector description of the progress of
the signal through the heart during a QRS interval. This vector
representation forms the basis upon which a doctor is trained to
understand and explain the outputs received at the various
electrodes in the 12-Lead system. Typically within a period of
about 0.08 seconds (one normal QRS interval), both ventricles are
depolarized and, as a result an electrical force is generated which
is characterized by a vector which depicts both the size and
direction of the electrical force. In electrocardiography, these
vectors are created sequentially over the entire QRS interval. The
normal plane for these vectors (i.e., the normal plane of
activation) is the same as the QRS cycle, i.e., perpendicular to
the X, Y plane (frontal) and slanted along the axis of the
heart.
In actuality, the muscle depolarizes from cell to cell and forms an
electrical wave front (a plane which separates tissue of different
electrical potential) as a function of time. This wave front can be
used to determine the resultant or mean vector whose magnitude,
direction and location can be determined by the summation of all
the small vectors which can be drawn perpendicular to the wave
front. The resultant or mean vector of all these vectors is the
resultant vector which is measured by the external electrodes and
is called the QRS vector. As can be appreciated, other mean vectors
are created over the other intervals in the ECG cycle in much the
same manner are termed appropriately, namely, the mean T-vector and
the mean P-vector.
Traditionally, it has been found that the force and direction of
the QRS vector would give an accurate representation of how the
heart was functioning over the period of the QRS interval. In order
to help determine the QRS vector in the frontal plane, a law was
developed by Einthoven which interrelated three (3) electrodes
specifically oriented on the body (right arm, left leg and left
arm). The signals between each two of the electrodes constituted a
"Lead". These leads formed a triangle known as Einthoven's triangle
and it was that these Leads could always be related to a single
vector in the frontal plane, i.e., any two signals when added
vectorally give a third vector. For diagnostic purposes these Leads
were later graphically translated into a triaxial system. Other
Leads were subsequently added to the triaxial system (i.e., termed
unipolar leads--a VR, a VL, and a VF) and a Hexial system was
developed. For simplification purposes, the system was displayed
out on a circle and degrees were later assigned to the various
leads of the system. FIG. 1a shows the circle which was developed
to represent the six Leads. This system is highly redundant.
In order for a physician to determine the mean QRS vector, the
physician would line up the various leads around the circle
according to their positivity or negativity and mark the transition
from positive to negative on the circle. This area of transition is
typically referred to as the "transition" area which when analyzing
a single plane, e.g., the frontal plane, is represented by a line
on the circle which separates the circle into positive and negative
halves. (See FIG. 1b). The mean QRS vector is positioned at a right
angle to the transition line on the positive side. (See FIG.
1b).
Using the above methodology, the direction and location of the mean
QRS vector on the circle determines how the heart is functioning
and allows a physician to ascertain typical heart malfunctions. For
example, in a normal adult, the mean QRS vector is usually located
between 0.degree. and 90.degree., i.e., between leads I and a VF on
the circle. However, a left axis deviation (LAD) is characterized
by the mean QRS vector being located in the 0.degree. to
-90.degree. area and with right axis deviation (RAD) the mean QRS
vector is located in the 90.degree. to 180.degree. area.
The mean T-vector and the mean P-vector are determined in a similar
manner. In fact, physicians have determined that one of the more
important elements of graphically illustrating the means QRS vector
and the mean T-vector is that the angle between the two vectors can
be easily ascertained. This angle relates the forces of ventricular
depolarization with the forces of ventricle repolarization. In a
normal adult, the angle between the mean QRS vector and the mean
T-vector is rarely greater than 60.degree. and most often below
45.degree..
Similarly, the mean P-vector can be determined. This enables a
physician to isolate the location of the electrical direction of
the excitation of the cardiac muscle of the atria.
The above analysis has been described using a single plane, namely
the frontal plane characterized by the superior, inferior, right
and left boundaries of the human body. In order for a physician to
analyze the overall movement of the heart muscle during
depolarization and repolarization, the physician needs to analyze
the vector forces along another plane, namely the horizontal plane
which is characterized by the posterior, anterior, right and left
boundaries of the human body.
Much in the same manner as described above, six leads are
positioned about the body to measure the electrical currents across
the heart muscle in the horizontal plane. These leads are typically
called the precordial leads and are represented as V1-V6,
respectively. Using the same methodology as described above with
respect to the frontal plane, the location and direction of the
mean QRS vector in the horizontal plane can also be determined.
When the two planes are analyzed simultaneously, the mean QRS
vector (and the other vectors) projects perpendicularly from the
transition "plane" rather than the transition "line" of the single
plane system. In other words, when the frontal plane and the
horizontal plane are isolated and individually analyzed, the mean
QRS transition appears as a line across the diameter of the circle.
In actuality this "line" is actually a "plane" when both systems
(frontal and horizontal) are analyzed simultaneously and the mean
vectors (QRS, T and P) project perpendicularly from this plane into
both systems.
As can be appreciated from the above summary, the analytical
process of determining the resultant QRS vector and the other
vectors can be quite cumbersome and requires a physician to
interpret various graphs and/or solve various formulas which tend
only to frustrate the diagnostic process and which can lead to
erroneous conclusions if analyzed improperly. For simplicity, most
physicians analyze each system individually at first and then
combine the results. However, as often is the case, the
determination of the mean vectors (QRS, T and P) in one plane is
still both time consuming and somewhat confusing. Further, trying
to determine how the mean vectors project into two planes and how
the angles between the vectors relate can be even more
confusing.
Moreover, even if a physician can adequately analyze the various
graphs and solve the various formulas to arrive at a diagnosis,
three-dimensional representation of the location of the mean QRS
vectors (and the other vectors) must be mentally visualized which
requires a high degree of mental agility and can lead to
misdiagnosis. Further, mentally visualizing the angles between mean
vectors would be virtually impossible for even the most skilled
physician. The additional problem of how these vectors change in
time over the QRS interval is believed to be nearly impossible to
consider by the prior methods.
In the past, several attempts have been made at resolving the above
problems. For example, 2-D vector cardiograms isolated the various
signals from the leads and used several oscilloscopes to show the
results in three planes (frontal, transverse (horizontal) and
sagittal). This has been studied in great detail and many texts
have been written to relate these diagrams to various heart
maladies. However, as far as is known no one has ever attempted to
display the signal as a series of 3-D vectors plotted at
intermittent time intervals over the duration of the signal, much
less represent these vectors on a single display and on a single
3-D coordinate system thereby producing a more easily identifiable
3-D view of the 12-Lead ECG signal or QRS complex as it progresses
through the cardiac muscle over time.
As can be appreciated, the above issues are exacerbated during
continual heart monitoring, e.g., monitoring patients in the
telemetry unit of a hospital. For example and as mentioned above,
continual heart monitoring utilizing a standard 12-lead display
system is a demanding process. As a result, heart monitoring is
usually automated such that slight changes in the electrical signal
from the heart are typically registered. A set of conditions are
programmed into the heart monitor and upon reaching a predetermined
threshold a bell or buzzer alerts the hospital staff. As is often
the case, false signals are generated which, as can be appreciated,
can be a tremendous waste of hospital resources. For example,
simple positional changes (i.e., a patient turns over to lie on
his/her side) often trips the heart monitoring alarm to alert the
staff of an ischemic condition. As can be appreciated, this can be
stressful on the hospital staff.
It would therefore be desirable to provide a device which can
overcome many of the aforesaid difficulties with diagnosing,
analyzing and monitoring heart malfunctions and provide devices and
methods which display heart maladies in an easily recognizable,
distinguishable, consistent and effective manner allowing even an
untrained observer to easily visualize, isolate and analyze common
heart conditions.
SUMMARY OF THE INVENTION
Accordingly, it is an object of the present invention to provide a
novel device and method which uses a vector description of the
progress of the signal through the heart during the QRS interval
which forms the basis upon which the doctor is trained to
understand the outputs received at the various electrodes in the
12-Lead system. The present disclosure relates to a of determining
an ischemic event and includes the steps of: monitoring and storing
an initial electrocardiogram vector signal (x, y, z) of a known
non-ischemic condition over the QRS, ST and T wave intervals;
calculating and storing a J-point of the vector signal and a
maximum magnitude of a signal level over the T wave interval;
monitoring a subsequent electrocardiogram vector signal over the
QRS, ST and T wave intervals; measuring and storing the magnitude
(Mag.) of the vector difference between a subsequent vector signal
and the initial vector signal; measuring and storing the angle
(Ang.) difference between a subsequent vector and the initial
vector at points; regressing a line from points about 25
milliseconds prior to the J point and about 60 milliseconds after
the J-point and determining the slope of the regression line and
the deviation of the angle difference of the regression line;
regressing a line from points about 100 milliseconds prior to the
maximum magnitude of the signal level over the T wave interval and
determining the slope of the regressing line and the deviation of
the angle difference of the regression line; and comparing the
slope and deviation of the lines from the J point and the T wave
interval to a set of known values to determine the presence of an
ischemic event.
In one embodiment, the step of measuring and storing the magnitude
(Mag.) of the vector difference includes the steps of: accessing
the stored initial electrocardiogram vector signal (x, y, z) of a
known non-ischemic condition over the QRS, ST and T wave intervals;
measuring the subsequent electrocardiogram vector signal (x, y, z)
over the QRS, ST and T wave intervals; calculating the change
(.DELTA.) in the vector signal over the QRS, ST and T wave
intervals by the following formula: .DELTA.x=x2-x1 .DELTA.y=y2-y1
.DELTA.z=z2-z1; and
calculating the magnitude of the vector difference (Mag.sub.vd)
over the QRS, ST and T wave intervals by the following formula:
Mag.sub.vd= (.DELTA.x.sup.2+.DELTA.y.sup.2+.DELTA.z.sup.2)
In another embodiment, the step of measuring and storing the angle
of the vector difference (Ang.) includes the steps of: accessing
the stored initial electrocardiogram vector signal (x, y, z) of a
known non-ischemic condition over the QRS, ST and T wave intervals;
measuring the subsequent electrocardiogram vector signal (x, y, z)
over the QRS, ST and T wave intervals; calculating the change
(.DELTA.) in the vector signal over the QRS, ST and T wave
intervals by the following formula: .DELTA.x=x2-x1 .DELTA.y=y2-x1
.DELTA.z=z2-x1;
calculating an azimuth angle (Az. Ang.) of the angle vector
difference over the QRS, ST and T wave intervals by the following
formula: Az. Ang.=arc tan(.DELTA.z/.DELTA.x); and calculating an
elevation angle (El. Ang.) of the angle vector difference over the
QRS, ST and T wave intervals by the following formula: El. Ang.=arc
tan(.DELTA.y/ (.DELTA.x.sup.2+.DELTA.z.sup.2)).
In still yet another embodiment according to the present method,
the step of calculating the J point includes the steps of:
calculating the magnitude of the initial vector signal (Mag.sub.vs)
over the QRS, ST and T wave intervals by the following formula:
Mag.sub.vs= (x.sup.2+y.sup.2+z.sup.2);
filtering the magnitude of the vector signal (Mag.sub.vs) over the
QRS, ST and T wave intervals through a low pass filter to establish
a smooth vector signal (VS.sub.sm) and a maximum value and time of
the QRS interval (QRS.sub.max and QRS.sub.maxtime); differentiating
the smooth vector signal (VS.sub.sm) from the magnitude of the
vector signal (Mag.sub.vs) over the QRS, ST and T wave intervals
and establishing a derivative vector signal (dVS.sub.sm);
calculating a set of initial parameters from the QRS interval
including: the magnitude of the maximum QRS signal (QRS.sub.max);
the maximum of the QRS time interval (QRS.sub.maxtime); and the end
point of the initiation of the QRS signal (QRS.sub.EndInit);
calculating a set of initial parameters from the T wave interval
including: the magnitude of the maximum T wave signal
(Twave.sub.max); and the maximum of the T wave time interval
(Twave.sub.maxtime); calculating an initial estimate of the end of
the QRS interval (QRS.sub.EndInit); fitting the vector signal along
a cubic polynomial curve; calculating the change in the derived
vector signal (dVS.sub.sm) over a prescribed time period to
establish a smooth test interval (S.sub.Test); fitting a first
order polynomial curve to the initial vector signal (Mag.sub.vs)
starting at the end of the QRS interval (QRS_EndInit) to a point
which is equal to the end of the QRS interval (QRS EndInit) plus
the smooth test interval (S.sub.Test); and calculating the
intersection of the cubic polynomial curve and the first order
polynomial curve and selecting a point of intersection that is
furthest from the time of the maximum QRS value (QRS.sub.maxtime)to
establish the J point.
The step of monitoring and storing an initial electrocardiogram
vector signal (x, y, z) of a known non-ischemic condition over the
QRS, ST and T wave interval may also include the step of:
estimating a magnitude and angle of the ST offset at the J point
and the J point plus sixty milliseconds (60 ms).
While apparently generally acceptable for their intended purposes,
so far as is known, none of the prior art devices display an
electrocardiograph heart signal in vector format within a single
three-dimensional coordinate system sampled at incremental time
intervals which comprises a point of origin and a three-dimensional
coordinate system comprising an x-axis, a y-axis and a z-axis
extending from the point of origin. The present disclosure further
includes a frontal plane defined by the area between the x-axis and
the y-axis, a sagittal plane defined by the area between the z-axis
and the y-axis and a transverse plane defined by the area between
the x-axis and the z-axis. The magnitude and location of the signal
are displayed within the coordinate system at incremental time
intervals using a plurality of vectors, the displaying mechanism
emanating from the point of origin.
It is also an object of the present invention to provide a device
which interprets the sampled data from an ECG digitally recorded
signal at certain time intervals and projects this signal as a
vector from a point of origin to a point in 3-D space as related to
the X, Y and Z axes. Such display information can include various
intervals and critical parameters relating to the ECG signal, e.g.,
P-wave, QRS interval including the initiation and end points of the
QRS interval, ST segment, J point, T wave, etc. In addition, other
information relating to the magnitude of the vector differences and
the angle (elevational and azimuth values) may also be displayed
relating to two ECG signal taken over a period of time. It is
envisioned that measuring, calculating and displaying this
information may lead to better analysis and heart monitoring
techniques.
The present disclosure also eliminates the step-by-step analytical
process of determining heart conditions and ischemic events and
provides a new techniques and new displays which are intended to
enhance recognition of the presence and type of malfunctions
related to the cardiac muscle.
As mentioned above, it is envisioned that the display can integrate
other information about the heart onto the same display which it is
believed will further enhance diagnostic analysis, e.g., a
calibrated display of the magnitude of the vector
(Magnitude=squareroot (X.sup.2+Y.sup.2+Z.sup.2)) for easier
evaluation of hypertrophy and possibly other conditions; displaying
the change in Magnitude from one vector to the next, which is
believed to be an indication of the continuity of heart muscle cell
activation and an additional indicator of disease; and displaying
the change in the angle of the heart vectors over the same time
interval which is believed to be a further indicator of muscle cell
activation and smoothness of transition of the depolarization of
cells over the myocardium.
By visually projecting the results of the 3-D heart vectors (and
accompanying information relating thereto) onto three planes,
namely, the frontal, the transverse and the sagittal planes, heart
analysis is greatly simplified and further enhanced. The display is
preferably color-coded to distinguish the vector sequence over the
QRS cycle, e.g., by color coding the time of occurrence of the
events in the QRS cycle, the ST offset, and the T-wave to clearly
show their inter-relationship and timing which is important to the
recognition of normal versus diseased conditions.
Further embodiments of the display allow a physician or medical
technician to manipulate the vector display to facilitate more
detailed examination of any portion of the vector sequence as a
function of time, e.g., the vector display may be expanded or
magnified to highlight and allow closer examination of certain
areas; the vector display may be shifted in steps both horizontally
and vertically from its present location; the vector display may be
rotated about the vertical axis 360 degrees, and elevated or
declined about the X-axis in steps; and the T-wave, P-wave or other
portion of the display may be removed if it interferes with the
observation of other portions of the signal.
These and other aspects of the present invention are described in
greater detail below.
BRIEF DESCRIPTION OF THE DRAWINGS
The file of this patent contains at least one drawing executed in
color. Copies of this patent with color drawing (s) will be
provided by the Patent and Trademark Office upon request and
payment of the necessary fee.
In the drawings, wherein similar reference characters denote
similar elements throughout the several views:
FIG. 1A is an illustration of the Hexial System showing the six
leads in the frontal plane;
FIG. 1B illustrates how the six Leads, I, II, III, a VR, a VL and a
VF are translated onto the IIexial System of FIG. 1a to graphically
depict the mean QRS Vector, the Transition Line, and the positive
side of the Transition Zone;
FIG. 2A is a 3-D vector cardiographic display of a normal heart
shown with several accompanying displays on a single screen;
FIG. 2Bb is the 3-D vector cardiographic display of FIG. 2a showing
the integration of surface modeling techniques between vectors;
FIG. 3 is a 3-D vector cardiographic display of a normal heart of
FIG. 2 at a 180.degree. azimuth showing the slant of the plane of
heart vectors;
FIG. 4A is a 3-D vector cardiographic display of a heart with left
ventricular hypertrophy;
FIG. 4B is the 3-D vector cardiographic display of FIG. 4a showing
the integration of surface modeling techniques between vectors;
FIG. 5A is a 3-D vector cardiographic display of a heart showing
anterior/inferior infarct along with several accompanying
displays;
FIG. 5B is an enlarged view of the 3-D vector cardiographic display
of FIG. 5a shown without the 12-Lead displays;
FIG. 5C is a highly enlarged view of the 3-D vector cardiographic
display of FIG. 5a highlighting the ST vector in the color red;
FIG. 6 is a 3-D vector cardiographic display of a heart showing
left bundle branch block;
FIG. 7 is a graphical display of a series of detectors of events
over 10 seconds for selection of a real time event to be displayed
in 3-D vector cardiographic format;
FIG. 8 is a 3-D cardiographic vector display of event No. 6 of FIG.
7;
FIG. 9 is a 3-D cardiographic vector display of event No. 7 of FIG.
7;
FIG. 10 is a 3-D cardiographic vector display of event NO. 8 of
FIG. 7;
FIG. 11 is a 3-D cardiographic vector display of event No. 9 of
FIG. 7;
FIG. 12 is a graphical representation of an electrocardiogram
showing the depolarization and repolarization of the heart muscle;
and
FIG. 13 is a graphical illustration of the x, y and z signal of an
ECG for an entire cycle with a J-point value of about 0.08
millivolts;
FIG. 14 is a graphical illustration of the x, y and z signal of an
ECG for an entire cycle with a J-point value of about 0.99
millivolts;
FIG. 15A is a plot of the magnitude of the vector difference
between a patient's normal ECG vector signal and an ischemic vector
signal;
FIG. 15B is a plot of the elevation angle and azimuth angle vector
difference between a patient's normal ECG vector signal and an
ischemic vector signal;
FIG. 16A is a plot of the magnitude of the vector difference of a
patient in a supine position and patient in lying on his right side
having circles denoting the average value over the J point and the
T wave regions, respectively;
FIG. 16B is a plot of the elevation and azimuth angles of a patient
in a supine position and patient in lying on his right side having
a series of linear regression lines to fit the J-point region and
the T wave region;
FIGS. 17A and 17B are plots of the magnitude difference and the
angle vector difference between a patient without ischemia followed
by an ischemic event;
FIG. 18 is a plot showing an example of an ECG signal with an
x-lead, y-lead and z-lead and showing the magnitude of the vector
sum;
FIG. 19 is a plot showing the raw magnitude of an ECG signal, a
filtered ECG signal and a derivative of the filtered signal;
FIG. 20 is a plot showing the raw magnitude of the ECG signal, the
ECG signal after a smoothing technique has been employed and a
cubic polynomial fit to the raw magnitude of the ECG signal which
is utilized to find a start point of the P wave of the ECG
signal;
FIG. 21 is a plot showing the raw magnitude of the ECG signal and
the polynomial fit to the raw magnitude of the ECG signal to find
the start of the QRS interval of the ECG signal;
FIG. 22 is a plot showing the raw magnitude of the ECG signal and a
cubic polynomial fit to the raw magnitude of the signal to find the
end of the QRS interval of the ECG signal which is the J point;
.Iadd.FIG. 22A is a plot showing the raw magnitude of the ECG
signal and a cubic polynomial fit to the raw magnitude of the
signal to find the end of the T wave;.Iaddend.
FIG. 23 is a plot showing the estimation of the ST offset in the
x-lead, y-lead and z-lead utilizing a straight line smoothing
technique;
FIG. 24A is an enlarged 3-D cardiographic vector display
highlighting a vector offset of a normal heart condition;
FIG. 24B is a greatly-enlarged 3-D cardiographic vector display due
to an ischemic condition highlighting a time period of prior to the
J point to the end of the T-wave;
FIGS. 25A-28 show various flow diagrams of the presently described
methods disclosed herein;
FIG. 29 shows the action potential across myocardial cells; and
FIG. 30 shows the action potential of a single cell at three points
in time.
.Iadd.FIG. 31 shows a computer readable medium (CRM) for storing
computer programmable instructions..Iaddend.
DETAILED DESCRIPTION
Conventional cardiographs display electrocardiograph heart signals
in vector format within a conventional coordinate system comprising
the "x" and "y" axes. The present disclosure relates to a vector
cardiograph coordinate system sampled at incremental time intervals
which comprises a point of origin and a three-dimensional
coordinate system comprising an x-axis, a y-axis and a z-axis
extending from the point of origin. As defined, the three
dimensional coordinate system includes a frontal plane defined by
the area between the x-axis and the y-axis, a sagittal plane
defined by the area between the z-axis and the y-axis and a
transverse plane defined by the area between the x-axis and the
z-axis. One such system is described in commonly-owned U.S. Pat.
No. 5,803,084 the entire contents of which is incorporated herein
in its entirety. The '084 patent discloses a displaying mechanism
which displays the magnitude and location of the signal within a
three dimensional coordinate system at incremental time intervals
using a plurality vectors wherein the displaying mechanism emanates
from the point of origin. For the purposes herein, only a brief
explanation of the above-identified patent is described as it
relates to the present disclosure.
FIGS. 2A and 2B show an example of a 3-D vector cardiographic
display 10 of the QRS interval of a normal heart. In this
particular case, the heart vectors 12 for the QRS interval are
determined at 1 ms intervals. The vectors 12 are color-coded over
20 ms time intervals so the sequence of the vectors 12 over the
entire QRS interval can be easily discerned. The color coding
sequence or map 30 can be selectively displayed by a physician when
needed.
It is believed that displaying the heart vectors 12 in this novel
fashion enables a physician to visually perceive critical
information for the diagnosis of heart disease. Displaying the
heart vectors 12 in this fashion also provides a good visual clue
as to the plane of the vectors 12 over the entire QRS interval,
which is also important for diagnosing heart disease. It is also
much easier to interpret the results of a 3-D vector
representation, since it relates directly to the orientation of the
heart in the body, and the deviation from a normal pattern becomes
immediately obvious even to the untrained observer.
FIG. 2A also combines the standard displays of the 12-Lead system,
the 2-D vectorgrams and the 3-D vector display. Preferably, the
accompanying displays do not interfere with the 3-D vector display
10 and are generally positioned at various locations around the
display 10. For example, in FIG. 2A the various Leads from the
12-Lead system are positioned around the 3-D vector display in a
general counterclockwise manner starting with the a VF lead at the
upper left corner of the display 10 following to the III lead at
the upper right corner of the display 10. Preferably, it is
possible for a physician to selectively manipulate any or all of
the lead displays or other accompanying displays to various
positions on the screen. Other accompanying displays can include
various graphs 32, 33, 34 representing, e.g., the changes in
magnitude and angle of the heart vectors and/or a display of the
color map for readily distinguishing the various vectors.
As can be appreciated from the present disclosure, a physician can
selectively determine which display he wants to view at any
particular time during the diagnosis. Further, it is within the
scope of the present invention to allow a physician to selectively
manipulate, e.g., magnify (zoom in), color, or rotate any one of
the displays at any given time. Although the 3-D vector display 10
is believed to be far superior than the other displays, by
combining the 3-D vector display 10 with theses other displays on a
single screen, it is believed that most, if not all, known heart
conditions can be readily observed. For example, by also projecting
the results or terminal points of the vectors 12 simultaneously
onto each of the three respective planes (frontal, transverse and
sagittal) of the 3-D vector display thereby forming 2-D vector
cardiographic projections 17, 18 and 19 on the same screen as shown
in FIGS. 2A and 2B, it is much easier for a physician to visualize
conditions that may be hidden on the 3-D display 10 without
rotating or expanding the display 10.
FIG. 2A illustrates the normal heart of FIG. 2A with the spaces
between vectors 12 filled and/or shaded. Preferably, these spaces
are color mapped in a manner similar to the vectors.
Advantageously, surface modeling and hidden line representation
techniques are employed to further enhance the picture.
FIG. 3 shows the normal heart of FIG. 2 which is rotated about a
180.degree. azimuth. As can be appreciated from the present
disclosure, a physician is able to manipulate the 3-D vector
cardiogram 10 for viewing purposes. For example, by rotating the
vector display of FIG. 2A, it is possible to observe that the
vectors 12 fall within a single plane. The angle of this plane can
be easily measured as an indicator of the orientation of the axis
of the heart in the body. As can be appreciated from the present
disclosure, the 3-D vector cardiogram 10 can be manipulated in many
fashions to view or highlight certain aspects of the display, e.g.,
the T-wave 42 can be readily observed as being oriented along the
same axis as the main axis of the QRS complex which characteristic
of a normal heart.
In contrast to this normal heart we show the case of a heart with
hypertrophy--i.e. enlarged heart muscle--shown in FIGS. 4A and 4B.
The QRS complex starts out in a normal manner over the first 25
milliseconds, then the magnitude increases very rapidly to a
maximum of 3 millivolts. As can be appreciated, an abnormal
condition is easily and immediately discernible which was not
necessarily the case with displays of the past.
In the case of FIG. 4A, the vector direction of this maximum
(anterior, inferior and left) and its time of occurrence could
indicated a enlargement of the muscles in the apex of the heart.
Diagnosis is left ventricular hypertrophy. Other parts of the ECG
signal and their respective locations and directions over the time
interval can also be easily and immediately identified. For
example, in FIG. 4A, the T-wave 42 is in the reverse vector
direction of the main axis of the heart, which is also an indicator
of hypertrophy. FIG. 4B illustrates the same heart using surface
modeling and hidden line techniques.
As can be appreciated from the present disclosure, the size, shape
and smoothness of this vector plane allows a doctor or technician
to immediately determine whether the patient has a healthy or
unhealthy heart, thereby expediting the task of making a proper
diagnosis. For example, if the display shows colors that represent
intervals of time over 100 ms, a physician will immediately know
that there is a problem, e.g., "Bundle Branch Block". Further, if
the physician observes that the plane of the heart vector diagram
is split into two planes, or, if the plane is above the x-axis,
again, the physician immediately recognizes that there is a problem
which is believed to be a myocardium infarction (as related to
coronary heart disease). As can be appreciated from the present
disclosure, analysis of the 3-D vector cardiographic display can
identify any number of other maladies more quickly that
conventional methods and may more accurately recognize maladies
previously unobserved. In addition, it is envisioned that the
presently disclosed 3-D vector cardiographic display coupled with
one or more of the presently-disclosed methods described herein may
enable more accurate analysis of non-ischemic versus ischemic
conditions during heart monitoring.
The vector direction of the T-wave 42 is important for diagnostic
purposes and, as can be appreciated, is immediately apparent from
the various figures, in particular, FIG. 4A. If the T-wave 42
points in the opposite direction to the main body of the QRS, a
problem is indicated. It is believed that the T-wave's 42 direction
is indicative of the location of infarction or ischemia that exists
in the diseased heart, i.e. anterior, lateral, inferior, or
posterior or combinations of these. The P-wave (not shown) can also
be integrated into the display (in a similar manner as the QRS
interval). This P-wave has diagnostic potential for functions of
the atrium of the heart, e.g., the initial electrical pulse form
the S-A node, and careful study of the P-wave when displayed in the
manner of the present invention may enable a physician to easily
pinpoint the location and/or problems with the atria.
Moreover, the detection (and display) of a patient's J-point (i.e.,
the junction between the end of the QRS and the beginning of the ST
segment) is a critical parameter for determining if a patient has
had an ischemic event (See FIGS. 24A and 24B). Typically, measuring
the J-point is a part of an initial screening process in the
Emergency Room at a hospital if the patient thinks that he/she has
had an ischemic event. A patient is typically put on an ECG to
determine if the J-point is elevated above his/her normal J-point
amount (if known or determinable) or the changes in the J-point
over time reach a certain threshold. In addition, as explained in
more detail below, the detection of the J-point is important for
other reasons as well, in particular, to help ascertain a false
ischemic condition (i.e., change in patient position) from a true
ischemic condition (e.g., heart attack).
It is believed that the display of the vectors 12 in small time
intervals, e.g., from about 0.5 ms to about 10 ms, provides
potential for diagnosing early signs of potential for ventricular
fibrillation and/or Ventricular tachycardia (VT). In has been seen
in some of the cases which exhibit severe myocardial infarction
that the vectors 12 over these regions are very irregular, i.e.,
the changes in magnitude and angle of the vectors are not smooth.
Studies of the movement of the excitation of heart muscle cells in
the region of infarction show that barriers exist to the smooth
conduction of muscle excitation. Several of the illustrated cases
of the present invention display these effects, namely, the
fluctuation of these vectors, which can be seen from their spatial
irregularity.
As mentioned above, additional displays 32, 33 and 34 can also be
selectively combined with the 3-D vector cardiograph 10 to show the
amplitude and angle fluctuations between successive vectors 12 of
the 3-D display 10. These displays 32, 33 and 34 are a measure of
the smoothness of the vector 12 motion and may provide additional
information of the degree of damage that may exist in the heart
muscle. The displays 32, 33 and 34 are calibrated in time with the
QRS interval and thus can be readily associated with the 3-D vector
display 10 to identify areas of roughness.
The magnitude of the vectors 12 calibrated in time over the QRS
interval is selectively displayed by graph 32 as seen in several of
the illustrations, e.g., FIG. 2A. As described in more detail
below, it is believed that the magnitude of the vectors 12 provides
a good measure of the maximum amplitude of the heart signal which
is an important tool in the diagnosis of heart conditions, e.g.,
left ventricular hypertrophy. Moreover and as explained in more
detail below, calculating the vector magnitude is an important step
for determining false heart conditions from true ischemic events.
In the case of the 12-Lead system, it is necessary to add the
levels from a number of the electrodes in order to gain an idea of
this amplitude, whereas this graphic display gives a direct
unambiguous measure.
Display 33 shows the change in magnitude between successive
vectors. It is believed that this change is a measure of the
smoothness of the traveling of the muscle cell excitation wave
front through the myocardium. Erratic changes are an indication of
disrupted or infarcted tissue and thus provides a qualitative
indication of tissue health. In addition and as explained in more
detail below with respect to FIGS. 13-23, calculating the
difference in magnitude between two ECG signals (e.g., an initial
or control ECG signal and a later monitored ECG signal (or parts of
each of the same)) is an important step in determining false heart
conditions and true ischemic events.
Display 34 shows the change in angle between successive vectors.
This is another measure of the character of the muscle cell
excitation wave front. This display reveals erratic changes which
are believed to be indicative of diseased tissue. This display also
shows rapid and fast changes in vector direction which it is
believed is indicative of the end of muscle excitation in one
region of the heart and transfer to another region. Measuring the
angle difference between an initial or base ECG signal and a
subsequent ECG signal is also an important step in determining
false heart conditions and true ischemic events.
Another illustration of heart disease is shown in FIG. 5A. In this
case there is definite indication of anterior heart disease. This
has been diagnosed from the 12-Lead data that is shown. The
deviation of the vector diagram 10 is also clearly shown. The
initial vector direction is right, then posterior, then a
progression towards the left, followed by a large increase to the
posterior, superior direction. This is shown in FIG. 5B and FIG. 5C
in larger display. The entire diagram could be produced by taking a
normal heart vector diagram and adding a vector in the opposite
direction of the anterior and inferior region of the heart whose
vectors are not being generated due to a loss of function. When the
QRS is completed it docs not return to zero but has an offset. This
offset can be incorporated into the 3-D display via an additional
vector 45 (color coded in bright red) as seen best in FIG. 5C. This
vector represents the end of the QRS interval and the very
beginning of the ST interval. It is believed that this vector 45
can be useful in the diagnosis of the location of ischemia or
infarction. As depicted by vector 45 in FIG. 5C, the magnitude and
direction of the ST voltage offset, if any, is easily recognizable
on the display because it is distinguished in color. In addition,
it is believed that the position and orientation of the vector 45
offset is useful for determining the location in the heart of the
failure, such as the coronary artery that is blocked, e.g., the
direction of the vector 45 points to the location of the ischemia.
The magnitude of this vector 45 is also useful since it has been
seen to relate to a recent ischemic episode. For example, in the
case illustrated in FIGS. 5A-5C, the vector 45 points to the
anterior and inferior location, which confirms the original
diagnosis from the direction of the disturbed QRS vector diagram.
As can be appreciated from the present disclosure, other indicators
than color may be employed to distinguish vector 45 or any other
vector 12, e.g., shading and/or varying the line weight and
type.
Another case is shown in FIG. 6 of a patient with LBBB (Left Bundle
Branch Block). This illustration shows the large amount of detail
that is available from the vector display 10 concerning the
sequence of excitation of the heart muscle in these cases. In the
case of LBBB the right ventricle is excited first by the Purkinje
right bundle. The muscle cells then conduct the depolarization
process to the left ventricle. The paths established in this manner
are different from the case of normal excitation. As a result, the
vector diagram is different from the normal case (See FIGS. 2A, 2B
and 3) as is obvious from the appearance of the display 10. One
result which is immediately perceivable is the fact that the
duration of the QRS signal is much longer than the normal QRS
process, which is the first criteria for BBB--i.e. the QRS complex
is longer than 110 ms.
It is also possible to apply the 3-D vector display 10 to data
taken in real time. FIGS. 7-11 shows some examples as a series of
3-D cardiograms shown from real time QRS and T-wave data shown for
a normal heart. These were consecutive heart cycles and are
interesting for the possible assessment of changing vector 12
characteristics from beat to beat as may be the case for ischemic
or infarcted tissue.
FIG. 7 shows the detection of the heart QRS complex by an algorithm
46 that looks at one of the X, Y or Z axis signals that has the
most rapid increase in signal level at the outset. The signal being
used is shown in the upper trace, in this case the X channel 50,
and the detector output 52 in shown in the lower trace. A ten
second interval is shown. The next four figures, i.e., FIGS. 8-11,
show the 3-D vectorgram 10 for events 6 through 9 depicted on FIG.
7. As can be appreciated from the present disclosure, there are
small variations from one 3-D display 10 to the next which it is
believed may prove to be useful in diagnosing certain disease
conditions.
FIGS. 13-28 relate to a method for detecting and monitoring
ischemic events. More particularly, the presently disclosed method
involves a so-called screening tool (Automatic or visual) which
allows physicians and hospital staff to quickly and accurately
distinguish between a true ischemic event and a false condition due
to patient positional changes.
The presently disclosed method involves the steps of: monitoring
and storing an initial electrocardiogram vector signal (x1, y1, z1)
of a known non-ischemic condition over the ECG signal (QRS, ST and
T wave intervals); calculating and storing a J-point of the vector
signal and a maximum magnitude of a signal level over the T wave
interval; monitoring a subsequent electrocardiogram vector signal
(x2, y2, z2) over the QRS, ST and T wave intervals; measuring the
magnitude (Mag.) of the vector difference between a subsequent
vector signal (x2, y2, z2) and the as initial vector signal (x1,
y1, z1); measuring the angle (Ang.) difference between a subsequent
vector (x2, y2, z2) and the initial vector signal (x1, y1, z1);
regressing a line from points about 25 milliseconds prior to the J
point and about 60 milliseconds after the J-point and determining
the slope of the regression line and the deviation of the angle
difference of the regression line; regressing a line from points
about 100 milliseconds prior to the maximum magnitude of the signal
level over the T wave interval and determining the slope of the
regressing line and the deviation of the angle difference of the
regression line; and comparing the slope and deviation of the lines
from the J point and the T wave interval to a set of known values
to determine the presence of an ischemic event (See Flow chart
FIGS. 25A and 25B). A more detailed explanation of the presently
disclosed method is described below with reference to FIGS.
13-24.
Other flow charts (See FIGS. 25-28) show the various additional
steps of the presently-disclosed method. For example, the step of
measuring and storing the magnitude (Mag.) of the vector difference
may include the steps of: accessing the stored initial
electrocardiogram vector signal (x1, y1, z1) of a known
non-ischemic condition over the QRS, ST and T wave intervals;
measuring the subsequent electrocardiogram vector signal (x2, y2,
z2) over the QRS, ST and T wave intervals; calculating the change
(.DELTA.) in the vector signal over the QRS, ST and T wave
intervals by the following formula: .DELTA.x=x2-x1; .DELTA.y=y2-y1;
.DELTA.z=z2-z1; and calculating the magnitude of the vector
difference (Mag.sub.vd) over the QRS, ST and T wave intervals by
the following formula: Mag.sub.vd=
(.DELTA.x.sup.2+.DELTA.y.sup.2+.DELTA.z.sup.2).
The step of measuring and storing the angle of the vector
difference (Ang.) may include the steps of: accessing the stored
initial electrocardiogram vector signal (x, y, z) of a known
non-ischemic condition over the QRS, ST and T wave intervals;
measuring the subsequent electrocardiogram vector signal (x, y, z)
over the QRS, ST and T wave intervals; calculating the change
(.DELTA.) in the vector signal over the QRS, ST and T wave
intervals by the following formula: .DELTA.x=x2-x1; .DELTA.y=y2-y1;
.DELTA.z=z2-z1; calculating an Azimuth angle (Az. Ang.) of the
angle vector difference over the QRS, ST and T wave intervals by
the following formula: Az. Ang.=arc tan(.DELTA.z/.DELTA.x); and
calculating an Elevation angle (El. Ang.) of the angle vector
difference over the QRS, ST and T wave intervals by the following
formula: El. Ang.=arc tan(.DELTA.y/
(.DELTA.x.sup.2+.DELTA.z.sup.2)).
As explained in more detail below with respect to FIGS. 13-24, the
step of calculating the J point includes the steps of: calculating
the magnitude of the initial vector signal (Mag.sub.vs) over the
QRS, ST and T wave intervals by the following formula:
##EQU00001## filtering the magnitude of the vector signal
(Mag.sub.vs) over the QRS, ST and T wave intervals through a low
pass filter to establish a smooth vector signal (VS.sub.sm) and a
maximum value and time of the QRS interval (QRS.sub.max and
QRS.sub.maxtime); differentiating the smooth vector signal
(VS.sub.sm) from the magnitude of the vector signal (Mag.sub.vs)
over the QRS, ST and T wave intervals and establishing a derivative
vector signal (dVS.sub.sm); calculating a set of initial parameters
from the .Iadd.smooth vector signal (V.sub.sm) in the .Iaddend.QRS
interval including: the magnitude of the maximum QRS signal
(QRS.sub.max); the maximum of the QRS time interval
(QRS.sub.maxtime); and the initial estimate of the end point of the
QRS signal (QRS.sub.Endinit).Iadd., the parameters also including
the initial estimated time of the start of the QRS signal
(QRS.sub.startInit) by finding the time before the time of
occurrence of the maximum smooth vector signal (VS.sub.sm) in the
QRS interval (QRSVS.sub.maxtime) that the derivative of the smooth
vector signal (dVS.sub.sm) changes polarity from negative to
positive (see FIG. 19); and the initial estimated time of
occurrence of the end point of the QRS signal (QRS.sub.EndInit) by
finding the time of occurrence after the time of occurrence of the
maximum smooth vector signal (VS.sub.sm) in the QRS interval
(QRSVS.sub.maxtime) at which the derivative of the smooth vector
signal (dVS.sub.sm) changes polarity from negative to positive (see
FIG. 19).Iaddend.; calculating a set of initial parameters from the
T wave interval including: the magnitude of the maximum T wave
signal (Twave.sub.max); and the maximum of the T wave time interval
(Twave.sub.maxtime); fitting the vector signal along a cubic
polynomial curve (a.sub.3x.sup.3+a.sub.2x..sup.2+a.sub.1x+a.sub.0)
.Iadd.from a point that extends from a point about midway between
the time of occurrence of the maximum smooth vector signal
(VS.sub.sm) in the QRS interval (QRSVS.sub.maxtime) through the
initial estimated time of occurrence of the end point of the QRS
signal (QRS.sub.EndInit) plus about 20 milliseconds (ms) at a
sample rate of 1 sample per millisecond (ms).Iaddend.; calculating
the change in the .[.derived.]. .Iadd.derivative of the smooth
.Iaddend.vector signal (dVS.sub.sm) over a prescribed time period
.Iadd.after the initial estimated time of occurrence of the end
point of the QRS signal (QRS.sub.EndInit) when the derivative of
the smooth vector signal (dVS.sub.sm) exhibits a substantially
constant magnitude .Iaddend.to establish a smooth test interval
(S.sub.Test) .Iadd.(See FIG. 19).Iaddend.; determining a point
where the polynomial curve begins to turn upward (point of
inflection which indicates the presence of the QRS) by examining
the coefficients of the fitted polynomial, i.e., a.sup.0 and
a.sup.1 where a.sup.1 is the slope of the curve (.mu.v/ms) and
a.sup.0 is the offset at the start of the curve; fitting a first
order polynomial curve to the initial vector signal (Mag.sub.vs)
starting at the end of the QRS interval (QRS_EndInit) to a point
which is equal to the end of the QRS interval (QRS_EndInit) plus
the smooth test interval (S.sub.Test); and calculating the
intersection of the cubic polynomial curve and the first order
polynomial curve and selecting a point of intersection that is
furthest from the time of the maximum QRS value (QRS.sub.maxtime)to
establish the J point .Iadd.as the end of the QRS interval
(QRS.sub.end).Iaddend..
.Iadd.Referring to FIG. 22, it should be noted with respect to the
fitting of the vector signal along a cubic polynomial curve
(a.sub.3x.sup.3+a.sub.2x..sup.2+a.sub.1x+a.sub.0) that the time of
occurrence of the maximum smooth vector signal (VS.sub.sm) in the
QRS interval (QRSVS.sub.maxtime) is offscale to the left of the
vertical axis "Signal Level in .mu.v" as illustrated by the arrow
designated "QRSmax time offscale". The point that extends from a
point about midway between the time of occurrence of the maximum
smooth vector signal (VS.sub.sm) in the QRS interval
(QRSVS.sub.maxtime) is illustrated by the arrow "Start Point for
Cubic Polynomial". The point of inflection that indicates the
presence of the QRS is with respect to the "Raw vector magnitude in
Red" as illustrated by the arrow "point of
inflection"..Iaddend.
After the step of monitoring and storing an initial
electrocardiogram vector signal (x1, y1, z1) of a known
non-ischemic condition over the QRS, ST and T wave intervals, the
method may include the step of estimating a magnitude and angle of
the ST offset at the J point and the J point plus sixty
milliseconds (60 ms). A more detailed explanation of estimating the
magnitude of the ST interval is explained below with reference to
FIGS. 23 and 28.
Turning now in detail to the presently disclosed method of
detecting and monitoring ischemic events as best shown in FIGS.
13-24, the basic method utilizes one of the characteristics of
ischemic tissue which tends to produce a current of injury with a
vector magnitude and direction. This underlying vector exists over
the entire QRS complex and the T-wave when the difference between
the action of the normal heart tissue and ischemic heart tissue are
compared. Put briefly, the vector difference between a non-ischemic
event and an ischemic event is used as a means of detecting the
ischemic event in an ECG monitoring environment. More particularly,
even though the vector difference exists over the entire QRS and
T-wave cycle in the case of extensive ischemia, a more sensitive
measurement for incipient ischemia is found by limiting the
examination to regions near the J point and prior to the peak of
the T-wave.
The analysis of the vector difference between a patient's reference
ECG (or initial ECG vector signal taken during his/her initial
emergency room visit or upon admission to a telemetry unit) and the
case of ischemia provides a magnitude and angular difference which
is found to be different in the case of a patient positional change
(e.g., supine to upright) and the case of ischemic events. The
presently-disclosed method includes a process for measuring,
detecting and exploiting these differences to distinguish between
non-ischemic events and ischemic events. It has been determined
that once the signals are analyzed, the key differences between the
two vector differences are the following: 1) the magnitude
differences tend to be smaller for non-ischemic events (e.g.,
positional changes); 2) the angular characteristic of the vector
difference over the region of the J point and the T-wave tend to be
substantially constant for the ischemic case and substantially
variable for non-ischemic events; 3) the fluctuations about the
mean square fit to the vector angle over the same regions tend to
be substantially large for non-ischemic events and relatively small
for the ischemic events.
Turning now in detail to the specifics of the presently disclosed
method, the ST offset that is normally used to distinguish the
presents of an ischemic event can be measured as vector offset to
the normal ECG. This vector offset exists for much of the QRS cycle
and also for the ST and T-wave segments of the ECG. Thus, it is
possible to use more data from the ECG signal for the detection of
the presence of an ischemic event. The method described herein
utilizes the x, y, z leads of the ECG (as described above with
respect to FIGS. 1-12) which are orthogonal axes for the
measurement of the ECG. These signals may be derived from the 12
lead signals by a number of transformation formulas (as described
above) and the x, y and z signals can be used to generate a vector
for each instant of time. This resulting vector can be represented
as a Magnitude and an Azimuth and Elevation angle. The presently
disclosed method utilizes a vector difference between non-ischemic
signals (from an initial or base ECG from a patient's initial or
from a known non-ischemic condition) and the ECG of the same
patient under observation such as in a telemetry unit of a
hospital. As can be appreciated, the presently disclosed technique
is particularly useful for monitoring those patients which tend to
have intermittent ischemic events. The reference pattern of x1, y1
and z1 signals over the QRS, T-wave interval are saved and recalled
to determine the difference in the actual x2, y2 and z2 signals and
the reference signal. Using a series of techniques described
herein, an ischemic vector over a portion of the QRS, T-wave
interval is ascertained to help distinguish between non-ischemic
and ischemic conditions.
More particularly, it is possible to look at the changes in the
vector between the non-ischemic heart condition and an ischemic
heart over the entire cycle from the beginning of the QRS to the
end of the T-wave. It has been shown that the electrical signal
from individual heart cells is altered by ischemia and is
manifested in the reduction of the electrical amplitude of the
intercellular voltage. The QRS cycle represents the period over
which myocardial cell activation begins. This reduction takes place
over the time from the beginning of the activation of the cell
depolarization to the cell's polarization. The cell action
potential remains at this elevated level for most of the time from
the beginning of the cell's activation over the QRS cycle to the
end of the cell's activation over the last part of the T-wave (See
FIGS. 29 and 30). Thus, it is possible to observe this effect for
the entire period when the non-ischemic reference state is
"subtracted" from the ischemic state. The most stable period is
near the end of the QRS cycle to the peak of the T-wave. FIGS.
13-15B shows an example of a subtraction technique which can be
used for this purpose using the orthogonal x, y, and z leads.
FIG. 13 shows a normal level of ST at the J point, i.e., a
non-ischemic condition having an ST offset at the J point of about
0.08 millivolts. FIG. 14 shows an ST magnitude of about 0.99
millivolts at the J point which is very high representing an
ischemic condition. The x1, y1, z1 data from the non-ischemic
condition is subtracted point for point from the x2, y2, z2 data
from FIG. 14 and the results show a difference vector which is
variable in amplitude but fairly constant in angle. ST offset
signals are called "currents of injury" and have been described as
the difference in the action potential in the normal cell and the
ischemic cell (See FIGS. 29 and 30). This action potential begins
at the point of excitation of the cell and ends when the cell is
fully re-polarized. Thus, the action potential starts at times over
the QRS interval and ends at times over the end of the T-wave. The
difference in the magnitude of the vector of the components is
shown in FIG. 15A. As can be appreciated, the signal is maximum
during the QRS, is slightly less at the J-point and increases again
at the peak of the T-wave. This may vary depending on the type of
ischemic condition that exists. FIG. 15B shows the azimuth and
elevation angles of the difference vector. More particularly, FIG.
15A shows the magnitude of the vector difference between the
patients normal ECG and the ischemic ECG over the QRS and T wave
intervals. FIG. 15B shows the Azimuth angle of the vector
difference in blue and the elevation angle of the vector difference
in red. Superimposed on these curves are two straight-line fits
400, 410 and 500, 510 to both the J point region and the T-wave
region, respectively. These are the best estimates for the curves
in region around the J point -25 ms to +60 ms, and around the T
wave maximum point to a point negative 100 milliseconds (-100 ms)
from the maximum.
As is evident, the ischemic cell structure is located in one region
which results in a vector signal in one direction. The initial
vector is very slightly different in angle which is believed to
represent an initial cell excitation pattern. Since the heart
myocardial cells are activated over the entire QRS cycle. The
initial action potential is very high and then levels off to a
slightly lower level. Even though this particular patient has a
very strong ischemic signal which is most likely also easy to
detect by conventional means, the strong ischemic signal also
illustrates that in an ischemic condition the vector difference
points in a substantially constant direction over the entire region
from about 25 milliseconds before the J point to the peak of the T
wave.
By applying this technique, the detection of an ischemic condition
at the onset (i.e., initial stages of ischemia) may be detected.
Moreover, this technique enables a physician, hospital staff or
automatic monitor to easily distinguish between those offsets
caused by the patient turning on his/her side and those offsets
caused by a true ischemic condition which is often a source of
false detection in the hospital monitoring situation. For example,
FIGS. 16A and 16B shows a patient who changed position from supine
to laying on his right side. As a result there is a change of the
ECG vectors over the period of the QRS to the end of the T wave.
FIG. 16A shows the magnitude of the difference vector where there
is a large change in the region of the QRS and then becomes small
at the J point. This is indicated by a first circle 450 and a light
vertical green line. The plot also shows an increased magnitude
over the T wave region. A second circle 550 shows the peak of the T
wave. The center of the circles 450, 550 is located at the average
level of the magnitude over the region of the straight-line fit to
the angle measurements shown FIG. 16B. The straight line fit to the
J point region (-25 ms before and 60 ms after) is shown as a red
line 480 for the Azimuth and a green line 460 for the Elevation
angle. These same colors are used for the straight line fit to the
T wave region, namely 485 (Az.) and 465 (El.). It is seen that
there is considerable fluctuation in these measurements and that
the slope is large. It has been determined that a substantially
large slope and a substantial amount of fluctuation is typical
during patient positional changes. It is contemplated that a slope
(or absolute magnitude of the slope) is greater than about 0.9
.mu.v/ms and a fluctuation is greater than about 15 .mu.v
(micro-volts).
FIGS. 17A and 17B illustrate a true ischemia condition (this
ischemic condition is to a much smaller extent than the file shown
in FIGS. 15A and 15B). The magnitude of the difference vector is
shown in FIG. 17A and is taken as the difference in the two
conditions of the patient before (i.e., non-ischemic) and after the
occurrence of an ischemic event. The straight line fit to the
Azimuth and Elevation angles (shown in red and green, respectively)
show a slope near zero and a small fluctuation of the raw data
about these estimates. It has been determined that a small slope
and small fluctuation in the angle difference is an indication of a
true ischemic condition. It is contemplated that during an ischemic
event, the slope (i.e., the absolute magnitude of the slope) is
less than about 0.9 .mu.v/ms and the fluctuation is less than about
15 .mu.v (micro-volts).
Table 1 below illustrates a comparison of Patient 1 (non-ischemic
event) and Patient 2 (true ischemic event) over 85 millisecond
across the J point and over the T wave.
TABLE-US-00001 T-wave Measurements over 100 ms J Point Measurements
over 85 ms T-wave T-wave T-wave T-wave T-wave ST Az ST Az ST Elev
ST Elev. ST Avg Az Az Elev Elev. Avg Patient Slope Std Slope Std
Ampl Slope Std Slope Std Ampl 1 -0.69022 15.171 -0.06584 21.486
58.4 -1.1975 29.69 0.36566 18.612 57.9 2 -0.1712 2.218 0.02425
5.696 166.3 0.50109 10.439 0.28949 8.706 324.8
The table above shows the clear distinction between Patient 1 and
2. Patient 1 represents a non-ischemic condition (e.g., a
positional change) and has high slope values and high standard
deviation about the straight line fit. The ST average amplitude for
Patient 1 is also small. The opposite is true for Patient 2, who is
having a true ischemic event. As can be appreciated, automating
these measurements of these key parameters makes it possible for
automatically monitoring these patients and reliably detecting the
onset of ischemic conditions. It is envisioned that this analysis
may be performed for each ECG signal which enables early detection
of a true ischemic condition and eliminates false ischemic
events.
One of the important features of the above process is the
determination of the ST offset and the J point at various
timeframes. It is contemplated that the detection of the J point in
an ECG is a critical parameter to enable proper measurement of the
ST offset which, in turn, enables a physician to reliably determine
if a patient has had an ischemic event. Typically, the detection of
the J point is part of a screening process which takes place in an
emergency room when a patient is admitted. These patients are
frequently put on an ECG monitor to determine if the J point is
elevated above a typical or normal amount (or the J point changes
from a patient's initial reading by a specific amount).
One of the major issues of ascertaining a good J point measurement
and the resulting ST offset is noise corruption typically
associated with other electronic equipment in an emergency room
setting. The presently proposed technique and method overcomes
noise issues utilizing a variety of smoothing and averaging
techniques which make use of the basic properties of the ECG signal
to differentiate between noise and the true ECG signal.
As mentioned above, in order to measure ST offset, an accurate J
point needs to be ascertained (as well as other critical points of
the ECG as explained below). A typical ECG recording is shown in
FIG. 18 and includes the x lead signal (red), the y lead signal
(dark green), the z lead signal (light green) and the Magnitude of
the vector (blue). The Magnitude (Mag.) of the vector is equal to
the square root of the sum of the squares of the x, y and z
signals: Magnitude= (x^2+y^2+z^2)
All of these signals tend to be very noisy, mostly in the regions
other than the QRS interval. It is known that the critical region
for a good measurement of the ST offset is immediately after the
end of the QRS interval (See FIG. 12), which tends to be a
relatively "noisy" region for all the leads (x, y, z) and the
Magnitude.
The presently disclosed method described herein improves the noise
level by passing the ECG signal through a low pass filter.
Preferably, a 10-Hertz Low Pass Remez FIR filter is used to
convolve the ECG signal with a balanced window function (See FIG.
19). The advantage of utilizing this type of filter is a good
smoothing effect without a phase shift which results in minimum
distortion of the true ECG signal by the low pass filter. Other low
pass filters known in the art are also envisioned. These filtered
signals provides reliable measurement points which may be used for
determining the best estimate of the start and end of the P-wave,
the QRS and the T-wave (See FIG. 19).
The maximum value of the QRS (QRS.sub.Max) is found from the
filtered signal since it is the largest of the signals to be found
in a single cycle of the ECG inclusive of the P-wave, the QRS
interval.Iadd., the ST interval .Iaddend.and the T-wave.
Substantially at the same time, a sample point of the maximum value
of the ECG .Iadd.in the QRS interval .Iaddend.is found along with
its .[.maximum value.]. .Iadd.magnitude (QRSmax) .Iaddend.and time
(QRS.sub.MaxTime) .Iadd.(See FIG. 19).Iaddend.. From .[.this point
forward.]. .Iadd.the time of occurrence of the maximum value of the
QRS interval (QRSmax) going in a reverse direction in time towards
the start of the single cycle of the ECG.Iaddend., the first "zero"
of the derivative of the smoothed .[.line.]. .Iadd.vector signal
(dVS.sub.sm) .Iaddend.is determined (i.e., the first sample point
where the derivative of the .[.smooth.]. .Iadd.smoothed vector
.Iaddend.signal.Iadd., or "Derivative of Smoothed Magnitude in
Green", .Iaddend.is zero) and that point is deemed the preliminary
.Iadd.or initial .Iaddend.start of the QRS signal (QRS.sub.StInit).
The next maximum of the ECG is then designated as the peak of the
P-wave (P.sub.waveMax) along with the P wave's time of occurrence
(P.sub.waveMaxTime). From this point, sample points are identified
where the derivative of the .[.smooth.]. .Iadd.smoothed vector
.Iaddend.signal .Iadd.(dVS.sub.sm) .Iaddend.is zero. This provides
additional points of departure for a more accurate measurement of
the P-wave start time (P.sub.waveStInit).
The initial point for the end of the P-wave (P.sub.EndInit) is
determined by looking forward (i.e., later in time) from the
P.sub.waveMaxTime and finding the sample point where the derivative
of the smooth curve is at its second "zero" or second minimum
value.
Using the P.sub.waveStInit value as a starting point, a polynomial
function is fitted in a least squares manner to the raw Magnitude
data (Mag.). By using the raw Magnitude data (Mag.), a best smooth
fit is determined to this section of the data which is adequately
approximated by a cubic polynomial. The results of this analysis
for a typical case are shown in FIG. 20. As shown in this figure,
the noise of the raw Magnitude (Mag.) curve is quite erratic
whereas the cubic polynomial fit is provides a central balanced
estimate of these sample points. The sample points located before
the beginning of the initial point P.sub.waveStInit, are used to
determine an average value of the signal before the P-wave. For
example, fifty sample points may be used to form the estimate of
the prior DC level (See FIG. 19) with the polynomial curve to find
a so-called "first crossing". This first crossing point is
determined as the start of the P-wave (P.sub.waveStart) which is
shown in FIG. 20 as the intersection of the horizontal magenta line
and the blue curve at point 24. This is the first point of
intersection of the P-wave curve starting at the maximum and
progressing to the start of the P-wave, which is found by the
presently-disclosed smoothing process.
Another similar technique may be used to find the end of the P-wave
(P.sub.waveEnd). In this case the end of the region between the
P.sub.endInit and the QRS.sub.stInit is averaged to find the
reference for the end of the P-wave (P.sub.QRSavg). At a point
after the peak of the P-wave, the maximum negative slope of the
smoothed Magnitude curve is determined. A line with the same slope
is projected from the point of this maximum negative slope to the
intersection with the P.sub.QRSavg. This intersection point is then
determined to be the end of the P-wave.
The start of the QRS (QRS.sub.Start) can be found in the same
manner as the P-wave start (P.sub.waveStart). The intersection of
the P.sub.QRSavg as a horizontal line with a polynomial fit to the
raw magnitude data (Mag.) is the start point for the QRS. An
example of these curves is shown in FIG. 21.
The detection of the end of the QRS interval is very important
because it is the point at which the ST offset is measured, i.e.,
the J point. The presently disclosed method utilizes the
combination of two (2) polynomial fittings: 1) the last part of the
QRS interval is fitted with a cubic polynomial due to the double
curvature of the data; and 2) the beginning of the ST curve of the
T-wave is best fitted with a straight line (linear regression). It
has been determined that the intersection of these two curves
defines the J-point which is considered the end of the QRS interval
and the beginning of the ST segment.
The initial sample point which is used at the onset of the analysis
is found from a smooth estimate of the raw magnitude vector (Mag.)
and the derivative of this smooth vector dVS.sub.sm. The sample
point after the peak of the QRS interval when the derivative of the
smooth vector magnitude dVS.sub.sm becomes a positive value plus
.about.20 ms (same as sample points at 1000 Hz sample rate) may be
used for the QRS interval end initiation point (QRS.sub.EndInit). A
cubic polynomial is thereafter fitted to the raw vector magnitude
data (Mag.) starting at the QRS.sub.EndInit and going back in
smaller values in steps of .about.10 ms. When the magnitude of the
polynomial coefficients of the so-called "a.sup.1" term is greater
than .about.30 .mu.v/ms (slope) or the magnitude of the so-called
"a.sup.0" term (constant term) minus the magnitude level at the
QRS.sub.EndInit is greater than .about.100 .mu.v (micro-volts) the
routine is stopped and the cubic polynomial coefficients from the
above analysis are later used for further analysis. A straight line
is fitted to the points beyond the QRS.sub.EndInit using initially
100 ms.
If the smoothed derivative of the smoothed data at the
QRS.sub.EndInit plus 100 ms minus the smoothed derivative at the
QRS.sub.EndInit point is greater than 2 .mu.v 1 ms then the
straight line estimate is recalculated over 50 ms instead of 100
ms. It is believed that this step helps rectify the unusual
situation when the ST segment of the T-wave has an initial
curvature (i.e., not a straight line).
The coefficients that are found using the above analysis for the ST
estimate are then extended beyond the initial point QRS.sub.endInit
to intersect the cubic curve. The point of intersection of these
two curves that is furthest from the QRS interval is chosen as the
final estimate of the end of the QRS interval and the beginning of
the ST segment (QRS.sub.End or J point). This is illustrated in
FIG. 22, where the intersection is found at point 30 ms.
.Iadd.As mentioned above and with particular respect to the T-wave,
it may be desirable to utilize the methods described above to
obtain an accurate and repeatable measure of the termination of the
T-wave. Such a measure may be easily accomplished by applying the
same principles utilized in the measurement of the beginnings and
endings of the P-wave and the QRS cycle. The T-wave has many of the
properties of the P-wave in that the T-wave changes slowly in time
and the low passed filtered signal does not deviate very far from
the true curve. For example, FIG. 12 illustrates the P wave
interval and the maximum value of the P wave (Pwavemax), which can
be seen as being similar to the T wave interval and the maximum
value of the T wave (Twavemax). The QRS cycle and the maximum value
of the QRS (QRSmax) occur between the P wave interval and the T
wave interval. These characteristics of the P wave, the QRS cycle
or interval, and the T wave can also be seen in FIG. 19. This
allows one to get a good estimate of the peak of the T-wave from
the derivative of the smooth estimate and to get a good starting
point for the estimate of the end of the T-wave (TwEndInit) from
the point where the smooth derivative of the vector signal
(dV.sub.sm) goes to zero. Similar to measuring the end of the QRS,
two polynomials are most suited to best measure the end of the
T-wave: (1) a cubic polynomial for the region of the T-wave before
the end which has a double curvature; and (2) a first order
polynomial to fit a straight line to the region after the end of
the T-wave (a post T-wave smooth test interval
(Post-Twsmoothtestinterval)). That is, the first order polynomial
is fitted to the post T-wave smooth test interval
(Post-Twsmoothtestinterval). The intersection of these two curves
can then be used as a repeatable and accurate measure of the end of
the T-wave..Iaddend.
.Iadd.This method is illustrated in FIG. 22A which shows the T-wave
of a typical ECG in which the Vector magnitude of the measured X, Y
and Z signals is drawn. Also shown is the smoothed magnitude of the
raw data in green. At the bottom part of the figure, the derivative
of the smoothed magnitude is shown in red. The peak of the T-wave,
(Twmax), is found at, or coincides with the time at which, the
point 101 on the red curve at which the derivative of the smoothed
magnitude curve is zero, i.e., about 670 milliseconds. At the next
point 102 on the red curve at which the derivative of the smoothed
magnitude (dV.sub.sm) curve is zero, i.e., about 774 milliseconds,
is found the initial or starting point for the analysis of the end
of the T-wave (TwTimeEndInit). At this point 102, an initial or
starting point is determined for the analysis of the end of the
T-wave (TwTimeEndInit). A cubic polynomial is fitted to the last
part of the T-wave curve to obtain an accurate measure of the true
value of the T-wave signal without noise, i.e., the derivative of
the smoothed data curve shown in red. The noisy signal or raw data
curve shown in blue is seen to be a deviation from the cubic
polynomial curve shown in red. The red cubic polynomial curve is
extended beyond the initial end point 102, by a pre-determined time
interval (e.g., about 20 milliseconds) to obtain a range of points
for more accurate end point determination. Also shown is a black
line which represents a first order polynomial fit to the region
after the initial end point, about +/- 20 milliseconds, to provide
an accurate estimate of the signal in this region. This black line
is extended back through the point of initial trial 102 to find a
point of intersection with the cubic polynomial curve illustrated
in red. This point of intersection is shown as the abscissa of
green vertical line 103, and measures the time in milliseconds of
the end of the T-wave. Thus, the point 101 is the time that the
derivative of the smoothed data (red curve) is zero, and is also
the time of occurrence of the peak of the T-wave, i.e., Twmaxtime.
Point 102 is the next zero value after the peak of the T-wave
(Twmax), or the T-wave initial end point and point 103 is the time
of the T-wave end (TwEnd)..Iaddend.
.Iadd.As previously described, the beginning of the QRS is
accurately measured for the same heart beat. The difference in time
between the end of the T-wave (TwEnd) and the start of the QRS
(QRSStart) is the QT interval. The QT interval is important for
determining if a patient is potentially susceptible to sudden
death..Iaddend.
Now that we know the beginning point of the ST segment is
determined by the above presently disclosed method, a more accurate
estimate of the ST parameters can be developed by the presently
disclosed methods described below. To do this we again utilize the
basic x, y and z data functions. Starting at the QRS.sub.End
determined from above, straight line fits 525, 535 and 545 to each
of these signals are calculated which determines a new best-fit
estimate for all the points in this region. Thus, a new smooth
estimate for the J point and also for the J point plus 60
milliseconds can be determined which are needed for the analysis
herein. These new smooth estimates are illustrated in FIG. 23
wherein each of the x, y and z signals are replaced in this region
by a straight line 525, 535 and 545, respectively, which forms the
best least mean square estimate of the data in this region. It is
clearly evident that there is a considerable variation of the raw
magnitude data about these smooth estimates. From these new
estimates, a vector is characterized which is represented by three
components, namely, magnitude, Azimuth angle and Elevation angle.
These components at the J point (453 ms) are calculated as follows:
Magnitude= (x(453)^2+y(453)^2+z(453)^2) Azimuth Angle=arc
tan(x(453)/z(453)) Elevation Angle=arctan(y(453)/
(x(453)^2+z(453)^2) These components are also calculated at the J
point (453 ms) plus sixty milliseconds (60 ms), i.e., 513 ms, using
the same formulas.
As a result, an estimation of the ST offset can be determined for
the J point and the J point plus sixty millisecond which, as
mentioned above, is an essential step for accurate for heart
monitoring.
Utilizing the above-identified method, a positional data set
representative of the non-ischemic state may be readily determined
along with a data set representative of a spontaneous ischemic
event. The method results in the automatic detection of a change
greater than about 100 micro-volts at the J point+60 ms in any of
the 12 leads of the normal ECG or the visual detection of such a
change as represented on a 3D vector cardiographic display such as
FIGS. 24A and 24B. As mentioned above, the occurrence of an
ischemic event is based on criteria determined from the magnitude
of the vector difference and the azimuth and elevation angle
consistency over the regions of the J point and the peak of the
T-wave. Therefor, the maximum change will always be found by the
vector magnitude whereas the 12 lead system may miss the maximum if
the vector is not in the same direction as any lead.
From the present description, those skilled in the art will
appreciate that various other modifications may be made without
departing from the scope of the present invention. For example,
while the display shows single line representations of the vectors
at various time intervals over the QRS signal, in some instances it
may be desirable to fill in the spaces between some or all of the
vectors with a solid color, e.g., modeling, which may, in some
circumstances, help in the visualization process. It is also
possible to employ the technique of rendering a 3-D surface so as
to show the effects of shading as the result of lighting from
various sources.
Although the various figures illustrate the QRS complex portion of
the ECG signal as a function time, it may be desirable to isolate
or highlight other portions of the ECG signal. In fact, it is
believed that other portions of the signal, if displayed in the
same or similar manner as the QRS signal, may show other heart
conditions which were difficult to easily recognize.
As noted in the illustrated cases, the QRS complex was sampled at 1
ms intervals. In some cases it may be desirable to sample the QRS
or another portion of the signal at longer or shorter intervals,
e.g., about 0.5 ms. In addition, the T-wave 42 interval is combined
on the same display and sampled at 5 ms intervals since this signal
does not change as rapidly. However, in some cases it may be
desirable to sample the T-wave 42 at shorter or longer intervals as
well.
.Iadd.The methods and processes disclosed and described herein may
be implemented in a processor-controlled device (e g., an
electrocardiography device), or display sub-system, as software
comprising one or more application programs executable within the
processor commonly known to reside within processor-controlled
devices (e.g., an electrocardiography device) or display
sub-systems..Iaddend.
.Iadd.In particular, the steps of the method of determining and
displaying the presence of an ischemic event, method for measuring
and displaying the J-point of an electrocardiogram signal and
method for determining and displaying from an electrocardiogram
signal at least one of the beginning and the end of the P-wave, the
P-wave duration, the start of the QRS interval, the end of the
T-wave, the QT interval, the PR interval and the QRS duration are
effected by instructions in the software that are executed by the
processor. The programmable instructions may be formed as one or
more code modules, each for performing one or more particular
tasks..Iaddend.
* * * * *