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.

Description

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.

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° and 90°, 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° to −90° area and with right axis deviation (RAD) the mean QRS vector is located in the 90° to 180° 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° and most often below 45°.

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 (Δ) in the vector signal over the QRS, ST and T wave intervals by the following formula:
Δx=x2−x1
Δy=y2−y1
Δz=z2−z1; and

calculating the magnitude of the vector difference (Mag_vd) over the QRS, ST and T wave intervals by the following formula:
Mag_vd=√(Δx²+Δy²+Δz²)

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 (Δ) in the vector signal over the QRS, ST and T wave intervals by the following formula:
Δx=x2−x1
Δy=y2−x1
Δz=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(Δz/Δx); 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(Δy/√(Δx²+Δz²)).

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_vs) over the QRS, ST and T wave intervals by the following formula:
Mag_vs=√(x²+y²+z²);

filtering the magnitude of the vector signal (Mag_vs) over the QRS, ST and T wave intervals through a low pass filter to establish a smooth vector signal (VS_sm) and a maximum value and time of the QRS interval (QRS_max and QRS_maxtime); differentiating the smooth vector signal (VS_sm) from the magnitude of the vector signal (Mag_vs) over the QRS, ST and T wave intervals and establishing a derivative vector signal (dVS_sm); calculating a set of initial parameters from the QRS interval including: the magnitude of the maximum QRS signal (QRS_max); the maximum of the QRS time interval (QRS_maxtime); and the end point of the initiation of the QRS signal (QRS_EndInit); calculating a set of initial parameters from the T wave interval including: the magnitude of the maximum T wave signal (Twave_max); and the maximum of the T wave time interval (Twave_maxtime); calculating an initial estimate of the end of the QRS interval (QRS_EndInit); fitting the vector signal along a cubic polynomial curve; calculating the change in the derived vector signal (dVS_sm) over a prescribed time period to establish a smooth test interval (S_Test); fitting a first order polynomial curve to the initial vector signal (Mag_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_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_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 (X²+Y²+Z²)) 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° 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;

smooth vector signal (V_sm) in the

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_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
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.

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.

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.

Claims

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 (Δ) in the vector signal over the qrs, ST and T wave intervals by the following formula:

Δx=x2−x1

Δy=y2−y1

Δz=z2−z1;

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 (Δ) in the vector signal over the qrs, ST and T wave intervals by the following formula:

Δx=x2−x1

Δy=y2−y1

Δz=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 (Δz/Δx); 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(Δy/√(Δx²+Δz²)).

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_vs) over the qrs, ST and T wave intervals by the following formula:

Mag_vs=√(x²+y²+z²);

filtering said magnitude of the vector signal (Mag_vs) over the qrs, ST and T wave intervals through a low pass filter to establish a smooth vector signal (VS_sm) and a maximum value and time of the qrs interval (qrs_max and qrs_maxtime);

differentiating said smooth vector signal (VS_sm) from said magnitude of the vector signal (Mag_vs) over the qrs, ST and T wave intervals and establishing a derivative vector signal (dVS_sm);

calculating a set of initial parameters from the qrs interval including: the magnitude of the maximum qrs signal (qrs_max1); the maximum of the qrs time interval (qrs_maxtime); and the end point of the qrs signal (qrs_EndInit);

calculating a set of initial parameters from the T wave interval including: the magnitude of the maximum T wave signal (Twave_max); and the maximum of the T wave time interval (Twave_maxtime); and

calculating an initial estimate of the end of the qrs interval (qrs_EndInit);

fitting the vector signal along a cubic polynomial curve;

calculating the change in the derived vector signal (dVS_sm) over a prescribed time period to establish a smooth test interval (S_Test);

fitting a first order polynomial curve to the initial vector signal (Mag_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_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_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.

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.

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 (Δ) 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:

Δx=x2−x1;

Δy=y2−y1;

Δz=z2−z1;

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.

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.

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.

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.

12. A method according to claim 6, wherein the initial electrocardiogram vector signal (x1, y1, z1) is (0, 0, 0).

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_vs), where each magnitude (Mag_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_vs) through a low pass filter to establish a smooth signal (VS_sm), a maximum value of the smooth signal (VS_sm) in the qrs interval (QRSVS_max) and a time of occurrence of the maximum value of the smooth signal (VS_sm) in the qrs interval (QRSVS_maxtime);

differentiating with respect to time the smooth signal (VS_sm) to establish a derivative of the smooth signal (dVS_sm) with respect to time;

calculating a set of initial parameters from the smooth signal (VS_sm) in the qrs interval including:

an initial estimated time of the start of the qrs interval (qrs_startInit) by finding the time before the time of occurrence of the maximum value of the smooth signal (Vs_sm) in the qrs interval (QRSVS_maxtime) that the derivative of the smooth signal (dVS_sm) changes polarity from negative to positive; and

an initial estimated time of occurrence of the end point of the qrs interval (qrs_endInit) by finding the time of occurrence after the time of occurrence of the maximum smooth signal (VS_sm) in the qrs interval (QRSVS_maxtime) at which the derivative of the smooth signal (dVS_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_endInit).

14. A method according to claim 13, further comprising the steps of:

fitting said sequence of magnitudes (Mag_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_maxtime) and the initial estimated time of occurrence of the end point of the qrs interval (qrs_endInit), to a sample at the initial estimated time of occurrence of the end point of the qrs interval (qrs_endInit);

calculating a change in the derivative of the smooth signal (dVS_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_endInit) to establish a smooth test interval (S_Test);

fitting a first order polynomial curve to said sequence of magnitudes (Mag_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_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_sm) in the qrs interval (QRSVS_maxtime), which intersection point is a true end of the qrs interval (qrs_trueend), and identifying the true end as the J point.

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.

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=((x²)+(y²)+(z²))^1/2

filtering the calculated magnitude signal (Mag) over the P-wave, qrs, and T-wave intervals to establish:

a smooth signal (VS_sm);

a time of occurrence of a maximum value of the smooth signal (VS_sm) during the P-wave interval (Pwmaxtime);

a magnitude of the maximum value of the smooth signal (VS_sm) during the P-wave interval (Pwmax);

a time of occurrence of the maximum value of the smooth signal (VS_sm) during the qrs interval (QRSVSmaxtime);

a magnitude of the maximum value of the smooth signal (VS_sm) during the qrs interval (QRSVSmaxtime);

a time of occurrence of the maximum value of the smooth signal (VS_sm) during the T-wave interval (Twmax); and

a magnitude of the maximum value of the smooth signal (VS_sm) during the T-wave interval (Twmaxtime);

establishing a derivative vector signal (dVS_sm) with respect to time of the smooth signal (VS_sm);

calculating from the smooth signal (VS_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_sm) changes from negative to positive, before the time of occurrence of the maximum value of the smooth signal (VS_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_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_sm) during the P-wave interval (Pwmax), the time of occurrence of the maximum value of the smooth signal (VS_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).

17. A method according to claim 16, further comprising the steps of:

calculating from the smooth signal (VS_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_sm) has a first zero value, before the time of occurrence of the maximum value of the smooth vector signal (VS_sm) of the electrocardiogram vector signal (x, y, z) during the qrs interval (QRSVSmaxtime).

18. A method according to claim 17, further comprising the steps of:

calculating from the smooth signal (V_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_sm) changes from negative to positive after the time of occurrence of the maximum smooth signal (VS_sm) during the T-wave interval (Twmaxtime).

19. A method according to claim 18, further comprising the steps:

fitting a first cubic polynomial curve to the smooth signal (VS_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_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_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).

20. A method according to claim 19, further comprising the steps:

fitting a second cubic polynomial curve to the smooth signal (VS_sm), from the time of occurrence of the maximum smooth signal (VS_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_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).

21. A method according to claim 20, further comprising the steps:

fitting a third cubic polynomial curve to the smooth signal (VS_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_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_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).

22. A method according to claim 21, further comprising the step of:

calculating the pr interval, using the following formula:

pr interval=QRSStart−PwStart.

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_sm) that extends from a point midway between the time of occurrence of the maximum smooth signal (VS_sm) in the Twave interval (Twmaxtime) and the initial estimated time of occurrence of the end point of the Twave interval (TwTimeEndInit).

24. A method according to claim 23, further comprising the steps of:

calculating a change in the derivative of the smooth signal (dVS_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_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_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_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).

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).