METHOD FOR STRESS DETECTION UTILIZING ANALYSIS OF CARDIAC RHYTHMS AND MORPHOLOGIES

Abstract

A method for detecting stress in organisms with a cardiac organ is provided. A cardiac waveform is input to an analysis system which decomposes the incoming signal to detect patterns within the decomposed segments. The patterns are comprised of one or more of the following: the overall waveform of a series of beats, a single beat or segments contained within a beat. The decomposed parts of the cardiac waveform are classified according to types of stress patterns both known in the art and dynamically learned through feedback. When the system detects that a sufficient threshold of stress has been exceeded, a notification can be generated and the details of the stress, such as the severity and type can be communicated to an external module, system, user or host. Patterns indicating a future or rapidly increasing stress level, signaled by evolving patterns in the cardiac waveform can be detected and an alert generated before a major or difficult to control stressful event is externalized by the organism.

Claims

1. A method of detecting stress employing correlation of cardiac waveform data to a stress pattern database.

2. The method of claim 1 wherein the method is configured to decompose and classify cardiac rhythms and correlate them against a stress pattern database for the detection of stress patterns.

3. The method of claim 1 wherein the method is configured to classify cardiac beats and correlate them against a stress pattern database for the detection of stress patterns.

4. The method of claim 1 wherein the method is configured to classify cardiac beat segments and correlate them against a stress pattern database for the detection of stress patterns.

5. The method of claim 1 wherein the method is configured to optionally classify cardiac rhythms, optionally classify cardiac beats or optionally classify cardiac beat segments and correlate them against a stress pattern database for the detection of stress patterns.

6. The method of claim 5 wherein the method is configured to detect patterns of ectopic beats and compare them against a stress pattern database for the detection of stress patterns.

7. The method of claim 5 wherein the method is configured to detect patterns of ectopic PVC beats and compare them against a stress pattern database for the detection of stress patterns.

8. The method of claim 5 wherein the method is configured to detect patterns of ectopic PAC beats and compare them against a stress pattern database for the detection of stress patterns.

9. The method of claim 5 wherein the method is configured to execute a special function when a stress threshold is exceeded.

10. The method of claim 5 wherein the method is configured to alert the user when a stress threshold is exceeded.

11. The method of claim 5 wherein the method is configured to alert a physician when a stress threshold is exceeded.

12. The method of claim 5 where in the method is configured to execute a physical action when a stress pattern is exceeded.

13. The method of claim 5 wherein an embodiment of the method is configured to reside on a flexible band containing surface monitoring electrodes.

14. The method of claim 5 wherein an embodiment of the method is configured to reside on a collar with surface monitoring electrodes.

15. The method of claim 5 wherein an embodiment of the method is configured to reside on a patch containing surface monitoring electrodes.

16. The method of claim 5 wherein an embodiment of the method is configured to be worn by a human.

17. The method of claim 5 wherein an embodiment of the method is configured to be worn by a non-human organism with a cardiac organ.

18. The method of claim 5 wherein an embodiment of the method is configured to be worn in conjunction with smart fabric.

19. The method of claim 5 wherein an embodiment of the method is adjusted with higher built in thresholds to be used in a predictively stressful state such as during counseling or surgery.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0033] FIG. 1 is a diagram of a cardiac biopotential differential voltage plot of a single heart beat.

[0034] FIG. 2 is a diagram of a cardiac biopotential differential voltage plot of a series of heart beats (cardiac rhythm) which is classified as a normal sinus rhythm (NSR).

[0035] FIG. 3 is a diagram of a cardiac biopotential differential voltage plot of a series of heart beats (cardiac rhythm) that contains four normal beats and two ectopic beats.

[0036] FIG. 4 is perspective view showing a series of monitoring devices connected via electrodes to a human.

[0037] FIG. 5 is perspective view showing a series of monitoring devices connected via electrodes to a dog.

[0038] FIG. 6 is a flow diagram showing a method of detecting stress and providing a notification.

DETAILED DESCRIPTION

[0039] A cardiac biopotential waveform is acquired 61 and presented to a decomposition and classification subsystem 62.

[0040] The decomposition and classification system 62 first detects segments of differing heart rhythms 63. Common examples may include normal sinus rhythm (NSR) FIG. 2, arterial fabulation (AFIB), ectopic rhythms FIG. 3, unknown rhythm or regions with no activity (pauses). The onset 30, offset 24, duration and other parameters (such as amplitude, frequency content, etc. . . . ) of each rhythm segment is calculated and stored 66.

[0041] After the differing heart rhythms are separated and classified 63, the resulting segments are further split into beats FIG. 1 by the decomposition and classification system 64. The onset 40, offset 45, duration and other parameters (such as amplitude, frequency content, ectopic status etc . . . ) of each beat segment is calculated and stored 66.

[0042] After the differing beats are separated and classified 64, the resulting segments such as those shown in FIG. 1 are further split into smaller waves 1, 2, 3, 4, 5, 6 segments 8, 11, intervals 7, and complexes 9 that form the isolated beat by a segment classifier 65. The waves, segments, intervals and complexes are analyzed for parameters such as amplitude, frequency content, shape, presence, ectopic classification, order etc. . . . and sent to a storage system 66.

[0043] The storage system 66 receives the data from the waveform and decomposition system 62 and makes it available to the comparison and pattern recognition system 66.

[0044] The comparison and pattern recognition system 67 compares the decomposed and classified rhythms, beats and segment and determines if and how much they are similar to a database of rhythms, beats and segments of an organism under stress. The comparison and pattern recognition system 67 computes a correlation coefficient between the current activity captured by the waveform acquisition system 61 and known or user indicated stress patterns.

[0045] The correlation coefficient or “stress score” is checked against a threshold 68 to determine if a notification is needed. If the threshold exceeds a predetermined or dynamically computed value a stress notification is triggered 69.

[0046] The system may process additional waveforms as they are acquired 61. The system may optionally reset between acquisitions or optionally incorporate the organisms specific stress responses into the stress database 66 to better predict and recognize future stressful patterns as they occur again.

[0047] Viable physical implementations of the stress detection system are possible in a diverse array of configurations. FIG. 4 details several locations on the human body where cardiac biopotential measurements are possible. On the wrist 52 a device is shown similar to watch that performs the processing described above and alerts the user upon a trigger threshold being exceeded 65. On the left clavicle 51 a cardiac monitoring device such as the Zio Patch manufactured by iRhythm Technologies could be programmed to monitor for stress using the methods described in this patent and alert the using upon reaching a trigger threshold 69.

[0048] A device containing the stress monitoring method could be placed near the waist 50.

[0049] Stress monitoring is also valuable for non-human organisms such as pets. FIG. 5 shows a system embodiment that is implemented as a monitor worn on a collar 81 of a dog. Other embodiments are possible such as patches worn near the heart 80.

[0050] Still further embodiments are possible for a device that monitors stress using the methods described in this patent. Possible options for device placement include anywhere that the cardiac electro cardiogram is viable such as the back, chest and neck regions. Given a sensitive enough monitor, placement almost anywhere on an organism is possible.

[0051] In an additional embodiment of the system, the system is configured to analyze a specific type of ectopic beat known as a PVC and correlate that to an organism's stress level. To achieve this, stress patterns related to PVCs are preloaded into the stress database 67. A waveform such as the one in FIG. 3 is acquired 61 and sent to a waveform decomposition and classification system 62. The rhythm is classified 63 as sinus arrhythmia. The onset and offset of the sinus arrhythmia rhythm is calculated 62 and stored 66. The rhythm segment is next decomposed into beats and which are classified and analyzed 63. Information about the beats are extracted from the classification of the beats. The information may optionally include the type of beat, the time of the beat, the frequency of similarly classified beats, the amplitude of the beat, the timing relationship to other beats, and the timing relationship between ectopic and normal beats.

[0052] In this example, two PVCs 41, 44 are detected by the beat classification system. The amount of time between the PVCs 41, 44 is calculated as well as the number of PVCs 41, 44 relative to the number of normal beats 40, 42, 43, 45. The classification, quantity and timing information is stored 66 for later correlation with the stress pattern database 68.

[0053] In this particular embodiment, the beat segments 65 are not classified. Other embodiments may optionally choose to use this data for the purposes of stress recognition.

[0054] The Waveform Decomposition data (which is comprised of the classified rhythm information and classified beat information), that has been stored 66 is then compared to a stress pattern database 67. In this embodiment a predetermined threshold of a ratio of PVCs 41, 44 to normal beats 40, 42, 43, 45 has been pre-programmed into the threshold detection and triggering system 68. In this example the threshold for the ratio of normal beats to PVC has been exceeded and a stress notification is triggered 69.