Apparatus and method for identifying myocardial ischemia using analysis of high frequency QRS potentials
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.
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 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; and
said alert comprises indicating ischemia.
2. A method according to claim 1 in which said analysis of a T-wave abnormality comprises detecting a T-wave inversion.
3. A method according to claim 1 in which said analysis of a T-wave abnormality comprises detecting a T-wave peakedness.
4. A method according to claim 1 in which said analysis of said low-frequency component of said ECG signal 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 more analysis of said low-frequency component of said ECG signal selected from a group consisting of:
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 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.
11. 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 perform analysis of a T-wave component in at least one QRS complex in a low frequency component 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 component,
wherein 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.
12. Apparatus according to claim 11 in which said analysis of said T-wave abnormality comprises detecting a T-wave inversion.
13. Apparatus according to claim 11 in which said analysis of said T-wave abnormality comprises detecting a T-wave peakedness.
14. Apparatus according to claim 11 in which said analyzing ECG signals comprises detecting an ischemic event.
15. Apparatus according to claim 11 , mounted as a wearable ECG monitor.
16. Apparatus according to claim 11 , configured as a part of an implantable device.
17. Apparatus according to claim 11 , configured as a part of an exercise stress test system.
18. Apparatus according to claim 11 , comprising a memory adapted to store a reference value from a different session.