SYSTEM AND METHOD FOR FACILITATING REFLECTOMETRIC DETECTION OF PHYSIOLOGIC ACTIVITY

• US 20130245437A1
• Filed: 03/14/2013
• Published: 09/19/2013
• Est. Priority Date: 03/19/2012
• Status: Active Grant

• Current Assignee: Advanced TeleSensors, Inc.
• Original Assignee: Advanced TeleSensors, Inc.
• Inventors: Gamble, Ronald C., Weill, Lawrence Randolph, Monacos, Steve Perry
• Granted Patent: US 9,492,099 B2
• Time in Patent Office: Days
• US Class Current: 600/430
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• 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 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/0507 using microwaves or terahertz waves
• CPC Class Codes: A61B 5/725 using specific filters therefor, e.g. Kalman or adaptive filters A61B5/316 take precedence
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• 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 method for remotely sensing cardiac-related data of an animal subject includes transmitting a RF signal to impinge on tissue of the subject, receiving a reflected portion of the RF signal, generating baseband data, filtering baseband data (e.g., including high pass filtering), performing waveform phase position determination, performing at least one auto-correlation of the waveform phase position determined data, determining periodicity of the auto-correlated data, and (i) computing heart rate using a maximum periodicity of the periodicity, or (ii) identifying abnormalities in cardiac function, such as may be indicated by temporal variations in heart rate and/or signal amplitude corresponding to cardiac activity. Multiple bandpass filtering schemes may be employed.

Claims

1. A method for remotely sensing cardiac-related data of an animal subject, the method comprising:

transmitting a radio frequency signal to impinge on tissue of the subject;

receiving a reflected radio frequency signal, the reflected radio frequency signal comprising a reflection of the radio frequency signal impinged on tissue of the subject;

generating baseband data utilizing the reflected radio frequency signal;

filtering data embodying or derived from the baseband data to yield initially filtered data, wherein said filtering includes high pass filtering with a cutoff frequency in a range of 10 Hz or greater to yield initially filtered data;

performing waveform phase position determination on data embodying or derived from the initially filtered data to yield waveform phase position determined data;

performing at least one auto-correlation of the waveform phase position determined data to yield auto-correlated data;

determining periodicity of data embodying or derived from the auto-correlated data; and

computing heart rate using a maximum peak of the periodicity.

2. A method according to claim 1, further comprising deriving either all positive values or all negative values from the initially filtered data, and then bandpass filtering the derived either all positive values or all negative values prior to said waveform phase position determination.

3. A method according to claim 2, wherein said bandpass filtering of the derived either all positive values or all negative values includes (i) low-pass filtering with a cutoff frequency of no less than 0.2 Hz and (ii) high-pass filtering with a cutoff frequency of no greater than 8 Hz.

4. A method according to claim 2, wherein said deriving either all positive values or all negative values comprises deriving all positive values, and said deriving of all positive values comprises squaring the initially filtered data.

5. A method according to claim 1, wherein said filtering of data embodying or derived from the baseband data to yield said initially filtered data comprises bandpass filtering including low-pass filtering with a cutoff frequency in a range of from 15 Hz to 50 Hz and high-pass filtering with a cutoff frequency in a range of from 15 Hz to 50 Hz, wherein the cutoff frequency of the low-pass filtering is no more than 2 Hz apart from the cutoff frequency of the high-pass filtering, and the cutoff frequency of the low-pass filtering is no greater than the cutoff frequency of the high-pass filtering.

6. A method according to claim 1, wherein said filtering of data embodying or derived from the baseband data to yield said initially filtered data comprises dual bandpass filtering comprising a bandpass including low-pass filtering with a cutoff frequency in a range of from 15 Hz to 50 Hz and including high-pass filtering with a cutoff frequency in a range of from 15 Hz to 50 Hz, wherein the cutoff frequency of the low-pass filtering is no greater than the cutoff frequency of the high-pass filtering.

7. A method according to claim 6, wherein the dual bandpass filtering comprises another bandpass that includes low-pass filtering with a cutoff frequency in a range of from 30 Hz to 70 Hz and includes high-pass filtering with a cutoff frequency in a range of from 5 Hz to 15 Hz.

8. A method according to claim 6, wherein each low-pass filtering and each high-pass filtering comprises use of filtering element characterized by a transfer function having a slope along the cutoff frequency of no less than a slope of a 4-pole Butterworth filter.

9. A method according to claim 1, wherein said filtering of data embodying or derived from the baseband data comprises obtaining multiple parallel streams of data embodying or derived from the baseband data, applying different filtering schemes to different data streams of the multiple parallel data streams, and comparing results of the different filtering schemes.

10. A method according to claim 1, further comprising performing analog-to-digital conversion of the baseband data and time segmenting the digitally converted data prior to said filtering to yield initially filtered data, wherein said filtering to yield initially filtered data comprises digital filtering.

11. A method according to claim 1, wherein said deriving of positive values from the initially filtered data comprises squaring the initially filtered data.

12. A method according to claim 1, wherein said performing of at least one auto-correlation of the waveform position determined data comprises performing dual auto-correlation.

13. A method according to claim 1, wherein determining periodicity of data embodying or derived from the auto-correlated data comprises performance of a Fast Fourier Transform calculation.

14. A method according to claim 1, wherein said computing of heart rate using a maximum peak of the periodicity comprises comparing an instantaneous heart rate value to (i) at least one previous periodicity or heart rate value, (ii) a value derived from a plurality of previous periodicity or heart rate values, or a median value derived from a plurality of previous periodicity or heart rate values.

15. A method according to claim 1, further comprising at least one of displaying and storing heart rate.

16. A method according to claim 1, wherein said receiving of the reflected radio frequency signal comprises one of the following schemes (i) and (ii):

(i) detection of a real signal component (I) and an out-of-phase signal component (Q), and wherein said baseband data comprises the real signal component (I) and the out-of-phase signal component (Q); and

(ii) detection of a real signal component (I) while an out-of-phase signal component (Q) is kept constant, and wherein said baseband data comprises the real signal component (I) without any out-of-phase signal component (Q).

17. A system for remotely sensing cardiac-related data of an animal subject, the system comprising:

a radio frequency transmitter adapted to transmit a radio frequency signal for impingement on tissue of the subject;

a radio frequency receiver adapted to receive a radio frequency signal comprising a reflection of the radio frequency signal impinged on tissue of the subject;

a baseband data generating element arranged to generate baseband data from the received radio frequency signal;

at least one filtering element arranged to filter data embodying or derived from the baseband data to yield initially filtered data, wherein said filtering includes high pass filtering with a cutoff frequency in a range of 10 Hz or greater to yield initially filtered data;

a waveform phase position determining element arranged to perform waveform phase position determination on data embodying or derived from the initially filtered data to yield waveform phase position determined data;

an auto-correlation element arranged to perform at least one auto-correlation of the waveform phase position determined data to yield auto-correlated data;

a periodicity determining element arranged to determine periodicity of data embodying or derived from the auto-correlated data; and

a heart rate computing element arranged to compute heart rate using a maximum peak of the periodicity.

18. The system of claim 17, further comprising an analog-to-digital converter arranged to convert analog baseband data to digital data prior to said filtering of data embodying or derived from the baseband data to yield initially filtered data, wherein said filtering of data comprises digital filtering.

19. The system of claim 17, wherein said filtering of data embodying or derived from the baseband data to yield initially filtered data comprises bandpass filtering including low-pass filtering with a cutoff frequency in a range of from 15 Hz to 50 Hz and high-pass filtering with a cutoff frequency in a range of from 15 Hz to 50 Hz, wherein the cutoff frequency of the low-pass filtering is no more than 2 Hz apart from the cutoff frequency of the high-pass filtering, and the cutoff frequency of the low-pass filtering is no greater than the cutoff frequency of the high-pass filtering.

20. The system of claim 17, wherein said filtering of data embodying or derived from the baseband data to yield initially filtered data comprises dual bandpass filtering comprising a bandpass including low-pass filtering with a cutoff frequency in a range of from 15 Hz to 50 Hz and including high-pass filtering with a cutoff frequency in a range of from 15 Hz to 50 Hz, wherein the cutoff frequency of the low-pass filtering is no greater than the cutoff frequency of the high-pass filtering.

21. The system of claim 17, comprising at least one processor arranged to execute a stored machine-readable instruction set, and the at least one processor comprises one or more of the following:

the at least one filtering element, the waveform phase position determining element, the auto-correlation element, the periodicity determining element, and the heart rate computing element.

22. The system of claim 17, wherein the at least one processor consists of a single microprocessor comprising each of the at least one filtering element, the waveform phase position determining element, the auto-correlation element, the periodicity determining element, and the heart rate computing element.

23. The system of claim 22, wherein the baseband generating element comprises a quadrature mixer arranged to process the received radio frequency signal with an oscillating signal representative of the transmitted radio frequency signal to output a real signal component (I) and out-of-phase signal component (Q).

24. A method for remotely sensing cardiac-related data of an animal subject, the method comprising:

transmitting a radio frequency signal to impinge on tissue of the subject;

receiving a reflected radio frequency signal, the reflected radio frequency signal comprising a reflection of the radio frequency signal impinged on tissue of the subject;

generating baseband data utilizing the reflected radio frequency signal;

filtering data embodying or derived from the baseband data to yield a plurality of sets of initially filtered data, wherein each set of initially filtered data is obtained by filtering including high pass filtering with a different filtering scheme;

performing waveform phase position determination on data embodying or derived from the plurality of sets of initially filtered data to yield a plurality of sets of waveform phase position determined data;

performing at least one auto-correlation of each set of the plurality of sets of the waveform phase position determined data to yield a plurality of sets of auto-correlated data;

determining periodicity of at least one set of data embodying or derived from the plurality of sets of auto-correlated data; and

computing heart rate from the periodicity.

25. A method according to claim 24, wherein said determining of periodicity comprises determining a plurality of periodicity values, and said computing of heart rate comprises selecting a majority or median of the plurality of periodicity values.

26. A method according to claim 24, wherein each different filtering scheme comprises at least one of (a) a different cutoff frequency, (b) a different filter transfer function slope, and (c) differing presence or absence of sequential filtering steps.

27. A method comprising:

transmitting a radio frequency signal to impinge on tissue of an animal subject;

receiving a reflected radio frequency signal, the reflected radio frequency signal comprising a reflection of the radio frequency signal impinged on tissue of the subject;

generating baseband data utilizing the reflected radio frequency signal;

filtering data embodying or derived from the baseband data to yield initially filtered data, wherein said filtering includes high pass filtering with a cutoff frequency of 10 Hz or greater to yield initially filtered data;

performing waveform phase position determination on data embodying or derived from the initially filtered data to yield waveform phase position determined data;

determining periodicity of data embodying or derived from the waveform phase position determined data, wherein the periodicity is indicative of cardiac activity; and

comparing periodicity indicative of cardiac activity for a selected interval to (i) periodicity indicative of cardiac activity for an interval preceding the selected interval and (ii) periodicity indicative of cardiac activity for an interval following the selected interval.

28. A method according to claim 27, wherein:

said filtering of data embodying or derived from the baseband data yields a plurality of sets of initially filtered data, wherein each set of initially filtered data is obtained by filtering including high pass filtering with a different filtering scheme;

said performing of waveform phase position determination on data embodying or derived from the initially filtered data yields a plurality of sets of waveform phase position determined data; and

said determining of periodicity of data embodying or derived from the waveform phase position determined data comprises determining periodicity of at least one set of data embodying or derived from the plurality of sets of waveform phase position determined data.

29. A method according to claim 28, wherein each different filtering scheme comprises at least one of (a) a different cutoff frequency, (b) a different filter transfer function slope, and (c) differing presence or absence of sequential filtering steps.

30. A method according to claim 28, further comprising identifying at least one temporal variation in periodicity indicative of cardiac activity based on results of the comparing step.

31. A method according to claim 30, further comprising performing at least one additional cardiac-related test on the animal subject based on identification of the at least one temporal variation.

32. A method according to claim 31, wherein the at least one additional cardiac-related test comprises any of:

a blood test, an electrocardiographic test, an impedance cardiographic test, an echocardiographic test, a phonocardiographic test, cardiac catherization imaging, an exercise stress test, and a pharmacological test.

33. A method according to claim 30, further comprising comparing information correlative of at least one temporal variation in periodicity indicative of cardiac activity with stored information correlative of at least one prior temporal variation in periodicity indicative of cardiac activity generated from the animal subject.