Determining heart rate

• US 7,135,002 B2
• Filed: 01/18/2002
• Issued: 11/14/2006
• Est. Priority Date: 01/25/2001
• Status: Expired due to Term

• Current Assignee: Sonomedical Pty., Ltd.
• Original Assignee: Sonomedical Pty., Ltd.
• Inventors: Sullivan, Colin Edward
• Primary Examiner(s): Pezzuto, Robert E.
• Assistant Examiner(s): Gedeon, Brian T.
• Application Number:
  US10/475,571
• Publication Number:
  US 20040267147A1
• Time in Patent Office: 1,761 Days
• Field of Search: 600/514, 600/528, 600/586, 128/901, 381/67
• US Class Current: 600/528
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/7239 using differentiation including higher order derivatives
• CPC Class Codes: A61B 7/005 Detecting noise caused by implants, e.g. cardiac valves
• CPC Class Codes: A61B 7/04 Electric stethoscopes microphones, acoustic transducers therefor H04R

Abstract

This invention concerns a method and system for automatically determining heart rate. The invention can be applied to determining the heart of any animal including humans. The method involves sensing body sounds and transducing them to electrical signals. Digitizing the electrical signals. Emphasizing the heart sound maxima (S1 and S2 signals) relative to noise by filtering, decompression and squaring. Detecting local maxima in the signals as likely S1 signals and generating a threshold amplitude. Selecting maxima that exceed the threshold as surviving likely candidate S1 signals. Screening the surviving candidate S1 against physiologically derived criteria. And, calculating the heart rate from the screened S1.

Claims

1. A method for automatically determining heart rate, comprising the steps of:

sensing body sounds and transducing them to electrical signals;

digitizing the electrical signals;

emphasizing the heart sound maxima (S1 and S2 signals) relative to noise by a first filtering step, decompression and squaring;

detecting local maxima in the signals as likely S1 signals;

generating a threshold amplitude;

selecting maxima that exceed the threshold as surviving likely candidate S1 signals;

screening the surviving candidate S1 against physiologically derived criteria; and

calculating the heart rate from the screened S1, wherein further filtering is performed after the decompression and squaring by a further low pass filter realised as a moving average FIR filter using triangular weighting.

2. A meted according to claim 1, where the first filtering step is performed using a first low pass filter having a cutoff at 60 Hz.

3. A method according to claim 1, where probable S1'"'"'s and S2'"'"'s are selected from those parts of the signal detected to be around maxima.

4. A method according to claim 1, where local maxima are detected by differentiating the signal.

5. A method according to claim 4, where the derivative is calculated as the first order difference.

19. A method according to claim 1, wherein local maxima are detected by differentiating the signal and wherein the signal is divided onto intervals, and the maximum with the greatest amplitude is taken for each interval and selected to be a likely S1.

20. A method according to claim 19, where if there is another maximum following in a suitable time window after the likely S1 in the same interval, then it is selected to be a likely S2.

21. A method according to claim 20, where the time window is between 160 ms and 400 ms.

22. A method according to claim 19, where, once a string of likely S1'"'"'s and S2'"'"'s have been recorded four histograms are constructed, namely histograms of the “

S1 amplitudes”

, the “

S2 amplitudes”

, the “

S1 to S1 intervals” and

the “

S1 to S2 intervals”

.

23. A method according to claim 19, where a threshold amplitude is generated for the likely S1'"'"'s using an “

S1 amplitudes”

histogram, and where any amplitude bin, or bins, on the histogram that show occurrence with a frequency greater than a physiologically derived upper limit, or threshold, are identified, and then, all the amplitude bins are discarded except those that have an amplitude greater than the amplitude of the bin(s) that have been identified.

26. A method according to claim 23, where once the likely S1'"'"'s have been reduced the S2'"'"'s are reduced to include only those detected in a predetermined time window after the surviving likely S1'"'"'s, and then the histograms are updated to include only the surviving likely candidate S1'"'"'s and S2'"'"'s.

27. A method according to claim 26, where likely candidate S1'"'"'s and S2'"'"'s are tested against the following criteria:

if a candidate S1 is wider than 250 ms at 80% of its peak value, or wider than 350 ms at 50% of its peak value, it is rejected.

28. A method according to claim 26, where likely candidate S1'"'"'s and S2'"'"'s are tested against the following criteria:

if other S1'"'"'s are not found within an expected time window or amplitude window on both sides of a candidate S1, it is rejected.

29. A method according to claim 28, where the time window is derived from a histogram of “

S1 to S1 intervals”

.

30. A method according to claim 28, where the amplitude window is derived from a histogram of “

S1 amplitudes”

.

31. A method according to claim 27, where likely candidate S1'"'"'s and S2'"'"'s are tested against the following criteria:

if the time since the preceding candidate S1 is less than the time until the next S1, the current candidate is presumed to be an S2, and it is rejected.

32. A method according to claim 26, where likely candidate S1'"'"'s and S2'"'"'s are tested against the following criteria:

if the time since the preceding candidate S1 is less than the largest S1 to S2 interval, seen from the histogram of“

S1 to S2 intervals”

, the current candidate is presumed to be S2, and it is rejected.

33. A method according to claim 26, where likely candidate S1'"'"'s and S2'"'"'s are tested against the following criteria:

if the ratio of the amplitude of a candidate S1'"'"'s to the amplitude of its S2'"'"'s is smaller or bigger than an expected window, the candidate is rejected.

6. A method for automatically determining heart rate, compromising the steps of:

sensing body sounds and transducing them to electrical signals;

digitizing the electrical signals;

emphasizing the heart sound maxima (S1 and S2 signals) relative to noise by filtering, decompression and squaring;

detecting local maxima in the signals as likely S1 signals by differentiating the signals;

generating a threshold amplitude;

selecting maxima that exceed the threshold as surviving likely candidate S1 signals;

screening the surviving candidate S1 against physiologically derived criteria; and

calculating the heart rate from the screened S1;

where local maxima are detected by differentiating the signal and

where the signal is divided onto intervals, and the maximum with the greatest amplitude is taken for each interval and selected to be a likely S1.

7. A method according to claim 6, where if there is another maximum following in a suitable time window after the likely S1 in the same interval, then it is selected to be a likely S2.

8. A method according to claim 7, where the time window is between 160 ms and 400 ms.

9. A method according to claim 6, where, once a string of likely S1'"'"'s and S2'"'"'s have been recorded four histograms are constructed, namely histograms of the “

S1 amplitudes”

, the “

S2 amplitudes”

, the “

S1 to S1 intervals” and

the “

S1 to S2 intervals”

.

10. A method according to claim 6, where a threshold amplitude is generated for the likely S1'"'"'s using an “

S1 amplitudes”

histogram, and where any amplitude bin, or bins, on the histogram that show occurrence with a frequency greater than a physiologically derived upper limit, or threshold, are identified, and then, all the amplitude bins are discarded except those that have an amplitude greater than the amplitude of the bin(s) that have been identified.

11. A method according to claim 10, where once the likely S1'"'"'s have been reduced the S2'"'"'s are reduced to include only those detected in a predetermined time window alter the surviving likely S1'"'"'s, and then the histograms are updated to include only the surviving likely candidate S1'"'"'s and S2'"'"'s.

12. A method according to claim 11, where likely candidate S1'"'"'s and S2'"'"'s are tested against the following criteria:

if a candidate S1 is wider than 250 ms at 80% of its peak value, or wider than 350 ms at 50% of its peak value, it is rejected.

13. A method according to claim 11, where likely candidate S1'"'"'s and S2'"'"'s are tested against the following criteria:

if other S1'"'"'s are not found within an expected time window or amplitude window on both sides of a candidate S1, it is rejected.

14. A method according to claim 13, where the time window is derived from a histogram of “

S1 to S1 intervals”

.

15. A method according to claim 13, where the amplitude window is derived from a histogram of “

SI amplitudes”

.

16. A method according to claim 11, where likely candidate S1'"'"'s and S2'"'"'s are tested against the following criteria:

if the time since the preceding candidate S1 is less than the time until the next S1, the current candidate is presumed to be an S2, and it is rejected.

17. A method according to claim 11, where likely candidate S1'"'"'s and S2'"'"'s are tested against the following criteria:

if the time since the preceding candidate S1 is less than the largest S1 to S2 interval, seen from the histogram of “

S1 to S2 intervals”

, the current candidate is presumed to be S2, and it is rejected.

18. A method according to claim 11, where likely candidate S1'"'"'s and S2'"'"'s are tested against the following criteria:

if the ratio of the amplitude of a candidate S1'"'"'s to the amplitude of its S2'"'"'s is smaller or bigger than an expected window, the candidate is rejected.

24. A system for determining heart rate, comprising an array of sensors to pick up the sounds and transform them to electrical signals, and a computer to digitize the signals and process them to detect S1 and S2, where the processing includes the steps of:

sensing body sounds and transducing them to electrical signals;

digitizing the electrical signals;

emphasizing the heart sound maxima (S1 and S2 signals) relative to noise by filtering, decompression and squaring;

detecting local maxima in the signals as likely S1 signals;

generating a threshold amplitude;

selecting maxima that exceed the threshold as surviving likely candidate S1 signals;

screening the surviving candidate S1 against physiologically derived criteria; and

calculating the heart rate from the screened S1;

the system further comprising;

a low pass filter realised as a moving average FIR filter using triangular weighting, to perform farther filtering after the decompression and squaring.

25. A system according to claim 24 further comprising a first low pass filter having a cutoff at 60 Hz to perform the filtering.