METHOD AND DEVICE FOR ESTIMATING MORPHOLOGICAL FEATURES OF HEART BEATS

• US 20110184297A1
• Filed: 01/26/2011
• Published: 07/28/2011
• Est. Priority Date: 01/26/2010
• Status: Active Grant

• Current Assignee: STMicroelectronics SRL (STMicroelectronics NV)
• Original Assignee: STMicroelectronics SRL (STMicroelectronics NV)
• Inventors: Pessione, Marco, Vitali, Andrea Lorenzo
• Granted Patent: US 8,909,332 B2
• Time in Patent Office: Days
• US Class Current: 600/509
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/346 Analysis of electrocardiograms
• CPC Class Codes: A61B 5/352 Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
• CPC Class Codes: A61B 5/7207 of noise induced by motion artifacts
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00

Abstract

A method estimates morphological features of heart beats from an ECG signal. Peaks of the R wave of the ECG are detected and classified using a parallel filtering structure. The first branch implements a bandpass filtering with cut off frequencies of about 10 Hz and 35 Hz, enhancing the signal-to-noise ratio (SNR) of the QRS complex. The second branch estimates morphological features of the heart beat from an alternating current (AC) replica of the ECG signal, that may be used to classify the beat and potentially detect arrhythmias.

Claims

1. A method, comprising:

filtering an electrocardiogram (ECG) signal with a passband filter with cut-off frequencies of about 10 Hz and 35 Hz, generating a corresponding passband signal;

filtering out a direct current component from said ECG signal, generating a corresponding alternating current (AC) signal; and

detecting occurrence of peaks of R waves of the ECG signal by processing the passband signal.

2. The method of claim 1, further comprising:

in response to detecting peaks of R waves of the ECG signal, generating estimations of the morphological feature of the heart beats by processing the AC signal, the morphological feature being one of a set consisting of width of QRS complex, height of peaks of R or P waves, and lengths of PR intervals.

3. The method of claim 2, wherein said estimations are generated by processing a replica of said AC signal blanked for an interval of about 50 ms after the occurrence of an R wave peak, according to the Hamilton-Tompkins algorithm.

4. The method of claim 1, wherein the filtering steps are performed on a digital replica of the ECG signal, and said peaks of R waves of the ECG signal are detected by:

processing said passband signal with a finite impulse response filter having a pulse response that is linearly increasing, generating an intermediate signal; and

establishing the detection of peaks of R waves at zero-crossings between two consecutive maxima of said intermediate signal.

5. The method of claim 1, wherein filtering out the direct current component from said ECG signal is performed before filtering the AC signal with the passband filter with cut-off frequencies of about 10 Hz and 35 Hz.

6. The method of claim 1, further comprising detecting disconnection from a patient of an electrode configured to detect the ECG signal, the detecting including determining that a number of samples of the ECG signal are above or below a useful signal range.

15. The method of claim 1, wherein the method further comprises detecting disconnection from a patient of an electrode configured to detect the ECG signal, the detecting including determining that a number of samples of the ECG signal are above or below a useful signal range.

7. A method, comprising:

detecting heart beats in an electrocardiogram (ECG) signal, the detecting including;

generating a corresponding passband signal by filtering a digital replica of the ECG signal with a passband filter with cut-off frequencies of about 10 Hz and 35 Hz;

generating an intermediate signal by processing said passband signal with a slope filter;

processing said intermediate signal with a moving average filter that generates a moving average of a number of samples of the intermediate signal; and

comparing said moving average with a threshold, establishing the detection of a heart beat when said threshold is surpassed.

8. The method of claim 7, further comprising:

detecting peaks of R waves of the ECG signal; and

in response to detecting peaks of R waves of the ECG signal, generating estimations of the morphological feature of the heart beats by processing the AC signal, the morphological feature being one of a set consisting of width of QRS complex, height of peaks of R or P waves, and lengths of PR intervals.

9. The method of claim 8, wherein said estimations are generated by processing a replica of said AC signal blanked for an interval of about 50 ms after the occurrence of an R wave peak, according to the Hamilton-Tompkins algorithm.

10. The method of claim 7, further comprising detecting disconnection from a patient of an electrode configured to detect the ECG signal, the detecting including determining that a number of samples of the ECG signal are above or below a useful signal range.

11. A computer readable memory medium storing processor instructions configured to cause a processor to execute a method comprising:

filtering an electrocardiogram (ECG) signal with a passband filter with cut-off frequencies of about 10 Hz and 35 Hz, generating a corresponding passband signal;

filtering out a direct current component from said ECG signal, generating a corresponding alternating current (AC) signal; and

detecting occurrence of peaks of R waves of the ECG signal by processing the passband signal.

12. The computer readable memory medium of claim 11, wherein the method further comprises:

in response to detecting peaks of R waves of the ECG signal, generating estimations of the morphological feature of the heart beats by processing the AC signal, the morphological feature being one of a set consisting of width of QRS complex, height of peaks of R or P waves, and lengths of PR intervals.

13. The computer readable memory medium of claim 12, wherein said estimations are generated by processing a replica of said AC signal blanked for an interval of about 50 ms after the occurrence of an R wave peak, according to the Hamilton-Tompkins algorithm.

14. The computer readable memory medium of claim 11, wherein the filtering steps are performed on a digital replica of the ECG signal, and said peaks of R waves of the ECG signal are detected by:

processing said passband signal with a slope filter, generating an intermediate signal; and

establishing the detection of peaks of R waves at zero-crossings between two consecutive maxima of said intermediate signal.

16. An ECG signal monitor, comprising:

a passband filter, with cut-off frequencies of about 10 Hz and 35 Hz, configured to filter an electrocardiogram (ECG) signal and generate a corresponding passband signal;

a DC filter configured to filter out a direct current component from said ECG signal and generate a corresponding alternating current (AC) signal; and

a peak detector configured to detect occurrence of peaks of R waves of the ECG signal by processing the passband signal.

17. The monitor of claim 16, further comprising:

a morphological feature extractor configured to, in response to being enabled by the peak detector, generate estimations of the morphological feature of the heart beats by processing the AC signal, the morphological feature being one of a set consisting of width of QRS complex, height of peaks of R or P waves, and lengths of PR intervals.

18. The monitor of claim 16, wherein the peak detector includes:

a slope filter configured to detect slope of the passband signal and generate an intermediate signal; and

a moving average filter configured to process said intermediate signal and generate a moving average of a number of samples of the intermediate signal.

19. The monitor of claim 16, further comprising:

a plurality of electrodes configured to detect an analog ECG signal of a patient;

an analog circuit configured to process the analog ECG signal; and

an analog/digital converter configured to convert the analog ECG signal to a digital ECG signal, wherein DC filter is configured to process the digital ECG signal

20. The monitor of claim 19, further comprising:

an electrode disconnect detector configured to detect disconnection of one or more of the electrodes from the patient by determining that a number of samples of the ECG signal are above or below a useful signal range.