APPARATUS AND METHOD FOR IDENTIFYING MYOCARDIAL ISCHEMIA USING ANALYSIS OF HIGH FREQUENCY QRS POTENTIALS

• US 20140031709A1
• Filed: 09/10/2013
• Published: 01/30/2014
• Est. Priority Date: 08/03/2006
• Status: Active Grant

• Current Assignee: BSP Medical Limited
• Original Assignee: Bsp Biological Signal Processing Ltd.
• Inventors: TOLEDO, Eran, Beker, Amir, Bregman-Amitai, Orna
• Granted Patent: US 8,862,211 B2
• Time in Patent Office: Days
• US Class Current: 600/521
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/366 Detecting abnormal QRS complex, e.g. widening
• CPC Class Codes: A61B 5/4884 inducing physiological or psychological stress, e.g. applications for stress testing
• CPC Class Codes: A61B 5/6804 Garments; Clothes
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/746 Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B

Abstract

Detecting cardiac ischemia by detecting local changes in high frequency ECG parameters. Local changes may be, for example, local reduction in RMS of high frequency components, for example, during a stress test.

Claims

1. A method for analyzing ECG signals, comprising:

(a) providing at least one ECG signal recorded from a body;

(b) having a computer determine the value of at least one time-varying parameter of a high frequency band of said ECG signal; and

(c) having a computer generate an alert responsive to a decision algorithm comprising a set of rules involving a combination of;

an instant variation of the time-varying parameter value during a test, wherein said instant variation is a change in the parameter value in comparison to the parameter value at a short time before; and

an analysis of a T-wave abnormality in at least one QRS complex in a low-frequency component of said ECG signal,

wherein said alert comprises indicating ischemia.

2. A method according to claim 1 in which said T-wave abnormality comprises a T-wave inversion.

3. A method according to claim 1 in which said T-wave abnormality comprises a T-wave peakedness.

4. A method according to claim 1 in which said analyzing ECG signals comprises detecting an ischemic event.

5. A method according to claim 1, wherein the ECG signal is sampled from a plurality of leads.

6. A method according to claim 5, wherein a lead with a high level of noise is discarded from the analysis.

7. A method according to claim 1, wherein said analyzing ECG signals comprises analyzing ECG signals in a monitoring setting.

8. A method according to claim 1, wherein said analyzing ECG signals comprises analyzing ECG signals in a stress-testing setting.

9. A method according to claim 1, and further comprising at least one analysis from a group comprising:

QRS duration of at least one QRS complex;

level of an ST segment of at least one QRST complex;

presence of an up-sloping ST segment in at least one QRS complex;

presence of a down-sloping ST segment in at least one QRS complex;

presence of a horizontal ST segment in at least one QRS complex;

QT interval duration in at least one QRS complex;

QTc interval duration in at least one QRS complex; and

PR interval duration in at least one QRS complex.

10. A method according to claim 1 in which said analysis of said low-frequency component of said ECG signal is performed in addition to any alignment of high frequency signals from said high frequency band of said ECG signal.

11. A method according to claim 1 in which said set of rules involves at least one of following:

a vector of primary indices, a vector of secondary HF indices, a vector of primary ECG indices and a vector of secondary ECG indices.

12. Apparatus for ECG signal analysis, comprising:

(a) an input for an ECG signal;

(b) a high-frequency band extractor which extracts a high frequency (HF) band from said signal;

(c) a filter configured to analyze said HF band and detect an instant variation, wherein said instant variation is a change in value of a time-varying parameter in comparison to the parameter value at a short time before;

(d) a processor configured to detect T-wave abnormality in at least one QRS complex in a low frequency components of said ECG signal, producing at least one physiological consideration; and

(e) an output which generates an output signal responsive to a decision algorithm comprising a set of rules involving a combination of the instant variation and the analysis of the low frequency components.

13. Apparatus according to claim 12 in which said T-wave abnormality comprises a T-wave inversion.

14. Apparatus according to claim 12 in which said T-wave abnormality comprises a T-wave peakedness.

15. Apparatus according to claim 12 in which said analyzing ECG signals comprises detecting an ischemic event.

16. Apparatus according to claim 12, mounted as a wearable ECG monitor.

17. Apparatus according to claim 12, configured as a part of an implantable device.

18. Apparatus according to claim 12, configured as a part of an exercise stress test system.

19. Apparatus according to claim 12, comprising a memory adapted to store a reference value from a different session.

20. A method for analyzing ECG signals, comprising:

(a) providing at least one ECG signal recorded from a body;

(b) having a computer determine the value of at least one time-varying parameter of a high frequency band of said ECG signal; and

(c) having a computer detect possibility of an ischemic condition responsive to a decision algorithm comprising a set of rules involving a combination of;

a variation of the time-varying parameter value during a test, wherein said variation is a change in the parameter value in comparison to the parameter value a short time before; and

an analysis of a T-wave abnormality in at least one QRS complex in a low-frequency component of said ECG signal.