HEALTH MONITORING SYSTEMS AND METHODS

• US 20150148691A1
• Filed: 12/09/2014
• Published: 05/28/2015
• Est. Priority Date: 10/07/2012
• Status: Active Grant

• Current Assignee: RDS
• Original Assignee: Rhythm Diagnostic Systems, Inc.
• Inventors: Moyer, Daniel Van Zandt, Golda, George Stefan, Marriott, Mark P., Eletr, Sam, O'Neil, Bruce
• Granted Patent: US 10,980,486 B2
• Time in Patent Office: Days
• US Class Current: 600/480
• CPC Class Codes: A61B 2560/0295 adapted for recording user messages or annotations
• CPC Class Codes: A61B 2560/0412 Low-profile patch shaped housings
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/0059 using light, e.g. diagnosis by transillumination, diascopy, fluorescence A61B5/0093, A61B5/1455, A61B5/02416 and A61B5/0261 take precedence
• 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 5/02125 of pulse wave propagation time
• CPC Class Codes: A61B 5/02141 Details of apparatus construction, e.g. pump units or housings therefor, cuff pressurising systems, arrangements of fluid conduits or circuits A61B5/02233, A61B5/0235 take precedence
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/0261 using optical means, e.g. infrared light
• CPC Class Codes: A61B 5/0295 using plethysmography, i.e. measuring the variations in the volume of a body part as modified by the circulation of blood therethrough, e.g. impedance plethysmography
• CPC Class Codes: A61B 5/08 Detecting, measuring or recording devices for evaluating the respiratory organs A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/14552 Details of sensors specially adapted therefor
• CPC Class Codes: A61B 5/259 using conductive adhesive means, e.g. gels
• CPC Class Codes: A61B 5/282 Holders for multiple electrodes for introduction into the body A61B5/287
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/335 using integrated circuit memory devices
• CPC Class Codes: A61B 5/352 : Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
• CPC Class Codes: A61B 5/6828 : Leg
• CPC Class Codes: A61B 5/6833 : Adhesive patches
• CPC Class Codes: A61B 5/72 : Signal processing specially adapted for physiological signals or for diagnostic purposes character recognition, recognising digital ink, document-oriented image-based pattern recognition G06V30/00; recognition or understanding of postal images G06V30/424
• CPC Class Codes: A61B 5/7207 : of noise induced by motion artifacts
• CPC Class Codes: A61B 5/721 : using a separate sensor to detect motion or using motion information derived from signals other than the physiological signal to be measured
• CPC Class Codes: A61B 5/7214 : using signal cancellation, e.g. based on input of two identical physiological sensors spaced apart, or based on two signals derived from the same sensor, for different optical wavelengths
• 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

Abstract

Systems, methods and devices for reducing noise in health monitoring including monitoring systems, methods and/or devices receiving a health signal and/or having at least one electrode or sensor for health monitoring.

Claims

1. A method for determining pulse transit time comprising:

generating one or more PPG frames from heartbeat information and one or more PPG signals;

creating a weighted, n-sample moving-average frame; and

,

determining the pulse transit time by finding the shift in the frame signal with respect to the heartbeat using the n-sample moving-average frame.

2. A method according to claim 1 wherein the pulse transit time is used to determine blood pressure.

3. A method according to claim 1 including using heartbeat information and one or more PPG signals to generate one or more PPG frames.

4. A method according to claim 3 where each frame contains the PPG signal of a single wavelength for the duration of one corresponding beat of the heart.

5. A method according to claim 1 including using ECG to generate heartbeat timing information by detecting the R-wave or other ECG feature from each beat.

6. A method according to claim 1 including performing a PPG signal quality estimate.

7. A method according to claim 6 wherein the PPG signal quality estimate uses one or more of PPG variance, estimated PPG signal-to-noise ratio, PPG signal saturation, patient motion accelerometer or gyroscope data, an ECG or impedance measurement noise estimate, or other information about the PPG signal quality.

8. A method according to claim 6 wherein the signal quality estimate is used in conjunction with the heartbeat timing information to generate the gain for each frame.

9. A method according to claim 8, where lower signal quality results in a lower gain.

10. A method according to claim 6 wherein the signal quality estimate is a constant used for the gain information.

11. A method according to claim 8 wherein the gain information is used with the frame information to create a weighted, n-sample moving-average frame.

12. A method according to claim 11, where the PPG signal that is correlated with the heartbeat timing is reinforced while the uncorrelated noise is reduced.

13. A method according to claim 11 wherein one or more of:

the number of samples included in the frame (n) are adapted to reduce noise or decrease response time;

the frames are additionally weighted by time in order to increase the contribution of recent or near-future frames with respect to frames that are further away and potentially less-relevant; and

,

the additional weighting by time is implemented using an IIR or FIR filter.

14. A method according to claim 11 further comprising determining the pulse transit time by finding the shift in the frame signal with respect to the heartbeat.

15. A method according to claim 11 further including one or more of:

finding the sample index where the signal is at a minimum or maximum and comparing it with the frame boundary (heartbeat timing) to determine the pulse transit time;

interpolating the signal using a spline or polynomial fit around the minimum or maximum values, allowing the minimum or maximum to be determined with greater precision than the sample rate;

or,

comparing the frame to a reference frame template, where the average frame is shifted with respect to the template;

wherein the shift with the highest correlation between the average frame and the template indicates the transit time;

wherein;

the reference template may be a predetermined signal, or

it may be allowed to adapt by using a long-term frame average with a known transit time.

16. A method according to claim 1 including one or both of performing a PPG signal quality estimate;

and the signal quality estimate is used in conjunction with the heartbeat timing information to generate the gain for each frame; and

, wherein

one or both of the PPG signal quality estimate and the gain information is used with the frame information to create a weighted, n-sample moving-average frame.

17. A method according to claim 1, where the PPG signal that is correlated with the heartbeat timing is reinforced while the uncorrelated noise is reduced.

18. A method according to claim 1 wherein one or more of:

the number of samples included in the frame (n) are adapted to reduce noise or decrease response time;

the frames are additionally weighted by time in order to increase the contribution of recent or near-future frames with respect to frames that are further away and potentially less-relevant; and

,

the additional weighting by time is implemented using an IIR or FIR filter.

19. A method according to claim 1 further comprising determining the pulse transit time by finding the shift in the frame signal with respect to the heartbeat.

20. A method according to claim 1 further including one or more of:

finding the sample index where the signal is at a minimum or maximum and comparing it with the frame boundary (heartbeat timing) to determine the pulse transit time;

interpolating the signal using a spline or polynomial fit around the minimum or maximum values, allowing the minimum or maximum to be determined with greater precision than the sample rate;

or,

comparing the frame to a reference frame template, where the average frame is shifted with respect to the template;

wherein the shift with the highest correlation between the average frame and the template indicates the transit time;

wherein;

the reference template may be a predetermined signal, or

it may be allowed to adapt by using a long-term frame average with a known transit time.

21. (canceled)

22. (canceled)

23. (canceled)