Health monitoring systems and methods

• US 10,244,949 B2
• Filed: 06/24/2016
• Issued: 04/02/2019
• Est. Priority Date: 10/07/2012
• Status: Active Grant

• Current Assignee: RDS SAS
• Original Assignee: Rhythm Diagnostic Systems, Inc.
• Inventors: Moyer, Daniel Van Zandt, Golda, George Stefan, Marriott, Mark P., Eletr, Sam, O'Neil, Bruce
• Primary Examiner(s): Gedeon, Brian T
• Application Number:
  US15/192,714
• Publication Number:
  US 20160302674A1
• Time in Patent Office: 1,012 Days
• Field of Search: None
• CPC Class Codes: A61B 2503/04 Babies, e.g. for SIDS detection
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• 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 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 2562/164 the sensor is mounted in or on a conformable substrate or carrier
• CPC Class Codes: A61B 2562/18 Shielding or protection of sensors from environmental influences, e.g. protection from mechanical damage
• 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 5/02 Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
• CPC Class Codes: A61B 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/02108 from analysis of pulse wave characteristics
• 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 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/02433 for infrared radiation
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/1135 by monitoring thoracic expansion
• CPC Class Codes: A61B 5/14546 : for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/1455 : using optical sensors, e.g. spectral photometrical oximeters
• 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 5/6823 : Trunk, e.g., chest, back, abdomen, hip
• CPC Class Codes: A61B 5/6833 : Adhesive patches
• 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 5/7246 : using correlation, e.g. template matching or determination of similarity
• 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 5/7278 : Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 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

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 a health parameter including one or more of detecting heart beats or determining pulse oxygenation;

the method comprising one or more of;

a) detecting heart beats;

using ECG,

using green or another wavelength, or

using a weighted combination of wavelengths;

b) determining pulse oxygenation through generating one or more of a first pulse shape template or a dataset representing a first pulse shape, including using;

green wavelengths,

an ensemble average of green over approximately the same amount of time as for either red or IR,

an ensemble average of multiple wavelengths over approximately the same amount of time as for either red or IR, or

an ensemble average of multiple wavelengths over significantly longer than the amount of time as for either red or IR;

or

a long time average of a single wavelength of any color;

c) obtaining a red pulse shape template or dataset representing same and an IR pulse shape template or dataset representing same, and comparing these or one or the other or each of these to the first pulse shape template; and

,

d) correlating via linear regression between a red ensemble average with a first pulse shape template or dataset to an IR ensemble average with the first pulse shape template or dataset, where the ratio of these correlations is then used as the AC ratio for oxygen saturation.

2. A method according to any of claim 1 wherein colors other than green or red or IR are used.

3. A method according to claim 2 wherein color selection is limited only by minimal effectiveness in one or both of signal to noise ratio or reflectiveness related to oxygenation.

4. A method according to any of claim 1 further comprising:

recording the first photoplethymogram PPG or ECG data in time-concordance with one or two or more additional photoplethysmographs of different light wavelengths;

detecting the heart beats in the first photoplethymogram PPG or ECG signal, these heart beats providing for definition of a frame of photoplethysmogram data for the time between two adjacent heart beats;

averaging two or more of these frames together at each point in time to create an average frame for the time interval;

wherein the photoplethysmograph PPG signal is reinforced by this averaging because the photoplethysmogram PPG signals are correlated with the heartbeat, and any motion artifact or other noise source that is uncorrelated in time with the heartbeat is diminished;

interpreting the signal-to-noise ratio of the average frame as typically higher than that of the individual frames;

using linear regression to estimate the gain between the two average frame signals;

estimating from this gain value one or more of the blood oxygen saturation or other components present in the blood including one or more of hemoglobin, carbon dioxide or others.

5. A method according to any of claim 1 wherein the operations are repeated for additional light wavelengths to estimate from the gain value one or more of the blood oxygen saturation or other components present in the blood including one or more of hemoglobin, carbon dioxide or others.

6. A method for health monitoring comprising:

sensing ECG signals by one or more ECG sensors and photoplethysmograph PPG signals by one or more optical sensors disposed on a single health monitoring device disposed on a body;

using a processor for;

determining from one or more or a combination of a user'"'"'s ECG or a first photoplethysmogram PPG signal or a weighted combination of wavelengths when heart beats occur, the weighted combination being of any number of different wavelengths of light as sensed by the optical sensors;

time averaging the first photoplethysmogram PPG signal to generate a first pulse shape template or dataset;

time averaging each of two additional photoplethysmogram PPG signals correlated to the beat locations;

one of the additional signals being a red signal, the other additional signal being an IR signal;

generating ensemble averages for each of the red and IR signals to obtain red and IR ensemble averages;

comparing each of the red and IR ensemble averages to the first pulse shape template or dataset to obtain red and IR ensemble average comparisons;

using a linear regression of each of the red and IR ensemble average comparisons to the first pulse shape template or dataset to determine the linear gain factor between the two signals;

determining from the linear gain factor the patient oxygen saturation.

7. A method according to claim 6 wherein the first photoplethymogram PPG signal is one or more of:

green, non-red;

non-infrared or a weighted combination of wavelengths.

8. A method according to claim 6 wherein the two photoplethysmogram PPG signals include one or more or all of green, red and infrared signals.

9. A method comprising:

selecting a possible gain value,

multiplying the average frame signal by it, and

determining the residual error with respect to an average frame of a different wavelength;

whereby the gain between red frame signals and infrared (IR) frame signals are found by;

generating one or more of green or other color PPG signals or a long time average of red and IR signals;

including the one or more of green or other color PPG signals or the long time average of red and IR signals with the red frame signals and infrared (IR) frame signals to create two frames;

averaging the two frames together first to provide a signal with reduced noise;

performing linear regression of the red versus combined with green or long time average of red and IR signals and infrared (IR) versus combined with green or long time average of red and IR signals;

or linear regression of red versus green or long time average of red and IR signals and infrared (IR) versus green or long time average of red and IR signals;

or linear regression by combining green or long time average of red and IR signals with each of the red frame signals and infrared (IR) frame signals and using the ratio of these results; and

then finding the ratio of the two corresponding results.

10. A method according to claim 9 for determining one or both of depth and rate of respiration.

11. A method according to claim 10 including

measuring IR or red or green reflection by the photodiode to estimate depth or rate of respiration.

12. A method according to claim 10 where one or both of:

maximum values and minimum values of a curve or waveform of the IR or red or green data represent the difference between the maximum and minimum values related to the depth of breath in an individual being monitored, and

over time, the rate of respiration is evaluated from the curve of maximum and minimum values over time.

13. A method according to claim 10 using PPG signals.

14. A method according to claim 13 including one or both:

obtaining the PPG signals when the chest expands and contracts during breathing, the motion hereof presenting as a wandering baseline artifact on PPG signals; and

,

isolating the respiration signal by filtering out the PPG data to focus on the breathing/respiration signal.

15. A method according to claim 13 wherein the PPG is chest-mounted.

16. A method according to claim 10 wherein any one or more of PPG and accelerometer methods are used discretely or in combination with each other or with the ECG-based respiration estimation techniques.

17. A method according to claim 10 wherein using multiple methods improves accuracy when compared to estimates based on a single method.

18. A method according to claim 10 wherein one or both:

one or more of ECG data, PPG data, pulse oximeter data and accelerometer data is used to determine respiration rate or depth of respiration; and

,

where one or more of red or IR or green values over time are used.

19. A method according to claim 18 including

generating, using the one or more of ECG data, PPG data, pulse oximeter data and accelerometer data, a respiration waveform.

20. A device using the method according to claim 9 wherein one or more of the signals are obtained from one or more of:

a wearable health monitoring device having;

a substrate;

a conductive sensor connected to the substrate, and

a double-sided composite adhesive having;

at least one conductive adhesive portion, and

at least one non-conductive adhesive portion;

the double-sided composite adhesive being attached to the substrate and the conductive sensor;

the at least one conductive adhesive portion being disposed in conductive communicative contact with the conductive sensor, and

being configured to be conductively adhered to the skin of the subject for conductive signal communication from the subject to the conductive sensor.