Real Time QRS Detection Using Adaptive Threshold

• US 20130237874A1
• Filed: 03/29/2012
• Published: 09/12/2013
• Est. Priority Date: 03/12/2012
• Status: Active Grant

• Current Assignee: Texas Instruments, Inc.
• Original Assignee: Texas Instruments, Inc.
• Inventors: Zoicas, Vasile
• Granted Patent: US 8,755,877 B2
• Time in Patent Office: Days
• US Class Current: 600/521
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/282 Holders for multiple electrodes for introduction into the body A61B5/287
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/352 Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
• CPC Class Codes: A61B 5/6805 Vests
• CPC Class Codes: A61B 5/6898 Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/725 using specific filters therefor, e.g. Kalman or adaptive filters A61B5/316 take precedence
• CPC Class Codes: A61B 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• 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

A mobile system for analyzing ECG data includes an analog front end module coupled to a mobile consumer device. The analog front end module is configured to collect ECG data from one or more leads and is operable to convert the analog ECG data to digital ECG data. The mobile consumer device is coupled to receive the digital ECG data, and is configured to perform QRS detection using a filter whose cutoff frequency is adapted to noise level in real time. The ECG signal is amplified non-linearly and three windowed threshold signals (D, E, J) are derived. The cutoff frequency for the QRS detection is dynamically selected as a function of the threshold signals. A sample in the amplified signal is identified to be a heart beat point only when the sample value is equal to the first threshold signal and greater than the filtered threshold signal.

Claims

1. A system comprising:

an analog front end module configured to collect ECG data from one or more leads and operable to convert the analog ECG data to digital ECG data; and

a mobile consumer device coupled to receive the digital ECG data, wherein the mobile consumer device is configured to perform QRS detection using a filter whose cutoff frequency is adapted to noise level in real time.

2. The system of claim 1, wherein the mobile consumer device is further configured to filter the digital ECG data and transmit the filtered digital ECG data in real time to a remote receiver.

3. The system of claim 1, wherein the mobile consumer device is further configured to detect a pre-alert condition by analysis of anomalies in the digital ECG data.

4. The system of claim 1, wherein the mobile consumer device is a smart phone.

5. A method for processing ECG data, the method comprising:

receiving a stream of raw ECG data samples comprising PQRST patterns;

filtering the raw ECG data to form filtered ECG data by using a non-linear filter to minimize baseline wander and to suppress a T wave portion of each PQRST pattern;

performing a non-linear operation on the filtered ECG data to form an amplified signal that exaggerates an R peak of each PQRST pattern;

deriving a first threshold signal and a third threshold signal using a moving max filter on the amplified signal;

deriving a second threshold signal using a moving average filter on the amplified signal;

filtering the third threshold signal to form a filtered threshold signal using a filter in which a cutoff frequency is dynamically selected as a function of the first threshold signal and the second threshold signal; and

identifying a sample in the amplified signal to be a heart beat point only when the sample value is equal to the first threshold signal and greater than the filtered threshold signal.

6. The method of claim 5, wherein filtering the raw ECG data comprises:

filtering the raw ECG data using a cascade of median filter and low pass filter;

delaying the raw ECG data; and

subtracting an output signal of the low pass filter from the delayed raw ECG data in order to deliver a high pass filtered data.

7. The method of claim 5, further comprising:

filtering the raw ECG data using a non-linear filter to minimize baseline wander of each PQRST pattern to form a viewable ECG signal; and

annotating the viewable ECG signal to indicate each heart beat point.

8. The method of claim 7, wherein filtering the raw ECG data comprises:

filtering the raw ECG data using a cascade of median filter and low pass filter;

delaying the raw ECG data; and

subtracting an output signal of the low pass filter from the delayed raw ECG data in order to deliver a high pass filtered data.

9. The method of claim 5, wherein the amplified signal is formed by squaring the filtered ECG data at least one time.

10. The method of claim 5, wherein filtering the third threshold signal comprises:

filtering the third threshold signal with a first order infinite impulse response (IIR) filter; and

dynamically selecting a cutoff frequency for the IIR as a linear function of a difference between a logarithm of the first threshold signal and a logarithm of the second threshold signal.

11. The method of claim 5, wherein filtering the third threshold signal comprises:

filtering the third threshold signal with a first order infinite impulse response (IIR) filter; and

dynamically selecting a cutoff frequency for the IIR as a linear function of a ratio of the first threshold signal and the second threshold signal.

12. The method of claim 5, wherein deriving a first threshold signal and a third threshold signal using a moving max filter on the amplified signal uses a first window width for the first threshold signal and a different window width for the third threshold signal.

13. A computer-readable non-transitory storage media having computer-readable instructions stored therein that when executed by a computer performs a method of processing ECG data in real time, the method comprising:

receiving a stream of raw ECG data samples comprising PQRST patterns from an analog front end coupled to the computer;

filtering the raw ECG data to form filtered ECG data by using a non-linear filter to minimize baseline wander and to suppress a T wave portion of each PQRST pattern;

performing a non-linear operation on the filtered ECG data to form an amplified signal that exaggerates an R peak of each PQRST pattern;

deriving a first threshold signal and a third threshold signal using a moving max filter on the amplified signal;

deriving a second threshold signal using a moving average filter on the amplified signal;

filtering the third threshold signal to form a filtered threshold signal using a filter in which a cutoff frequency is dynamically selected as a function of the first threshold signal and the second threshold signal; and

identifying a sample in the amplified signal to be a heart beat point only when the sample value is equal to the first threshold signal and greater than the filtered threshold signal.

14. The computer-readable non-transitory storage media of claim 13, wherein filtering the raw ECG data comprises:

filtering the raw ECG data using a cascade of median filter and low pass filter;

delaying the raw ECG data; and

subtracting an output signal of the low pass filter from the delayed raw ECG data in order to deliver a high pass filtered data.

15. The computer-readable non-transitory storage media of claim 13, further comprising:

filtering the raw ECG data using a non-linear filter to minimize baseline wander of each PQRST pattern to form a viewable ECG signal;

annotating the viewable ECG signal to indicate each heart beat point; and

displaying the annotated viewable ECG signal on a display coupled to computer.

16. The computer-readable non-transitory storage media of claim 13, wherein the amplified signal is formed by squaring the filtered ECG data at least one time.

17. The computer-readable non-transitory storage media of claim 13, wherein filtering the third threshold signal comprises:

filtering the third threshold signal with a first order infinite impulse response (IIR) filter; and

dynamically selecting a cutoff frequency for the IIR as a linear function of a difference between a logarithm of the first threshold signal and a logarithm of the second threshold signal.

18. The computer-readable non-transitory storage media of claim 13, wherein filtering the third threshold signal comprises:

filtering the third threshold signal with a first order infinite impulse response (IIR) filter; and

dynamically selecting a cutoff frequency for the IIR as a linear function of a ratio of the first threshold signal and the second threshold signal.

19. The computer readable non-transitory storage media of claim 13, wherein the computer readable storage media is comprised within a smart phone.

20. The computer readable non-transitory storage media of claim 13, wherein the computer readable storage media is comprised within a medical system.