Methods for generating data output containing physiological and motion-related information

• US 9,314,167 B2
• Filed: 11/21/2014
• Issued: 04/19/2016
• Est. Priority Date: 02/25/2009
• Status: Active Grant

• Current Assignee: Valencell, Inc.
• Original Assignee: Valencell, Inc.
• Inventors: LeBoeuf, Steven Francis, Tucker, Jesse Berkley, Aumer, Michael Edward
• Primary Examiner(s): FULLER, RODNEY EVAN
• Application Number:
  US14/550,039
• Publication Number:
  US 20150105633A1
• Time in Patent Office: 515 Days
• Field of Search: 600/310
• US Class Current: 1/1
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
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• CPC Class Codes: A61B 2560/0443 Modular apparatus
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 2562/0233 Special features of optical sensors or probes classified in A61B5/00
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• CPC Class Codes: A61B 5/002 Monitoring the patient using a local or closed circuit, e.g. in a room or building A61B5/0017 takes precedence
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/0024 for multiple sensor units attached to the patient, e.g. using a body or personal area network
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• 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 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• 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 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/02427 : Details of sensor
• CPC Class Codes: A61B 5/02433 : for infrared radiation
• CPC Class Codes: A61B 5/026 : Measuring blood flow A61B3/1233, A61B3/1241 take precedence
• 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 5/0816 : Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/091 : Measuring volume of inspired or expired gases, e.g. to determine lung capacity
• 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 5/1107 : Measuring contraction of parts of the body, e.g. organ, muscle apparatus for measuring work or force in general G01L
• CPC Class Codes: A61B 5/1118 : Determining activity level
• CPC Class Codes: A61B 5/14532 : for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/1455 : using optical sensors, e.g. spectral photometrical oximeters
• CPC Class Codes: A61B 5/14551 : for measuring blood gases
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• 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 5/7221 : Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• CPC Class Codes: A61B 5/725 : using specific filters therefor, e.g. Kalman or adaptive filters A61B5/316 take precedence
• CPC Class Codes: A61B 5/7278 : Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• CPC Class Codes: A61B 5/7282 : Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61B 5/742 : using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/7475 : User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: G02B 6/0001 : specially adapted for lighting devices or systems lighting or signalling on vehicles using light guides B60Q1/00; lighting devices for vehicle dashboards B60Q3/10; lighting devices for vehicle interior using light guides B60Q3/62; lighting devices mounted on the vehicle rear part using light guides F21S43/235; measuring arrangements having light conducting pointers G01D13/265; illumination of liquid crystal displays G02F1/1336; illuminated signs G09F13/00
• CPC Class Codes: G16H 20/30 : relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 30/40 : for processing medical images, e.g. editing
• CPC Class Codes: G16H 40/63 : for local operation
• CPC Class Codes: G16H 40/67 : for remote operation
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems
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• CPC Class Codes: Y02A 90/10 : Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

A method of generating a data string containing physiological and motion-related information includes sensing physical activity of a subject via at least one motion sensor attached to the subject, sensing physiological information from the subject via at least one photoplethysmography (PPG) sensor attached to the subject, and processing signals from the at least one motion sensor and signals from the at least one PPG sensor into a serial data string of physiological information and motion-related information. A plurality of subject physiological parameters can be extracted from the physiological information, and a plurality of subject physical activity parameters can be extracted from the motion-related information. The serial data string is parsed out such that an application-specific interface can utilize the physiological information and motion-related information for an application that generates statistical relationships between subject physiological parameters and subject physical activity parameters in the physiological information and motion-related information.

Claims

1. A method of generating data output containing physiological and motion-related information, the method comprising:

sensing physical activity and physiological information from a subject via a single monitoring device attached to the subject, wherein the monitoring device comprises at least one motion sensor for sensing the physical activity and at least one photoplethysmography (PPG) sensor for sensing the physiological information; and

processing signals from the at least one motion sensor and signals from the at least one PPG sensor, via at least one processor, into a serial data output of physiological information and motion-related information,

wherein the serial data output is configured such that a plurality of subject physiological parameters comprising subject heart rate and at least one of subject heart rate variability, subject blood gas level, subject blood flow, subject blood pulse volume, subject blood analyte levels, subject breathing rate, subject breathing volume, subject blood oxygen levels, subject blood pressure, subject VO₂max, the 1st derivative of at least one subject blood pulse, and the 2nd derivative of at least one subject blood pulse can be extracted from the physiological information, and such that a plurality of subject physical activity parameters can be extracted from the motion-related information.

2. The method of claim 1, wherein the serial data output is parsed out such that an application-specific interface (API) can utilize the physiological information and motion-related information for an application.

3. The method of claim 1, wherein the application is configured to generate statistical relationships between subject physiological parameters and subject physical activity parameters in the physiological information and motion-related information.

4. The method of claim 3, wherein the application is configured to generate statistical relationships between subject physiological parameters and subject physical activity parameters via at least one of the following:

principal component analysis, multiple linear regression, machine learning, and Bland-Altman plots.

5. The method of claim 1, further comprising, prior to processing signals from the at least one motion sensor and signals from the at least one PPG sensor into the serial data output, removing frequency bands from the PPG signals that are outside of a range of interest using at least one band-pass filter to produce pre-conditioned PPG signals, and filtering the pre-conditioned PPG signals to reduce motion artifacts and noise artifacts from the pre-conditioned PPG signals to produce cleaner physiological information.

6. The method of claim 5, wherein the subject motion noise comprises subject footstep noise.

7. The method of claim 5, wherein filtering the preconditioned PPG signals comprises at least one of the following:

FIR (Finite Impulse Response) filtering, IIR (Infinite Impulse Response) filtering, adaptive filtering, phase filtering, and frequency filtering.

8. The method of claim 1, wherein the at least one motion sensor comprises at least one of the following:

an optical sensor, an inertial sensor, an electrically conductive sensor, a capacitive sensor, an inductive sensor, an accelerometer, and a blocked channel sensor.

9. The method of claim 1, wherein the at least one PPG sensor comprises at least one optical emitter, at least one optical detector, and at least one light guide.

10. The method of claim 1, wherein the at least one motion sensor and the at least one PPG sensor are integrated into a wearable device.

11. The method of claim 10, wherein the wearable device is configured to be attached to the subject at one or more of the following body locations:

an ear, a limb, the nose, and a digit.

12. The method of claim 1, wherein the at least one motion sensor and the at least one PPG sensor are integrated into a chipset.

13. The method of claim 1 wherein the physiological information and/or motion-related information comprises information on data integrity.

14. A method of monitoring a subject via a monitoring device attached to a body of the subject, the device comprising at least one optical emitter and at least one optical detector, the method comprising:

directing light having a plurality of optical wavelengths at the body of the subject via the at least one optical emitter;

measuring body motion of the subject by detecting, via the at least one optical detector, light scattered by the body that is within a first wavelength range, wherein the first wavelength range comprises violet light or ultraviolet (UV) light; and

measuring blood vessel changes or blood analyte levels of the subject by detecting, via the at least one optical detector, light scattered by the body that is within a second wavelength range different from the first range, wherein the second wavelength range comprises green light, red light, infrared (IR) light or blue light.

15. The method of claim 14, wherein the monitoring device is configured to be attached to the subject at one or more of the following body locations:

an ear, a limb, the nose, and a digit.

16. A method of monitoring a subject via a monitoring device attached to a body of the subject, the device comprising at least one motion sensor and at least one photoplethysmography (PPG) sensor, the method comprising:

directing light having a plurality of optical wavelengths at the body of the subject via the at least one PPG sensor;

measuring body motion of the subject by detecting, via the at least one motion sensor, light scattered by the body that is within a first wavelength range, wherein the first wavelength range comprises violet light or ultraviolet (UV) light; and

measuring blood vessel changes or blood analyte levels of the subject by detecting, via the at least one PPG sensor, light scattered by the body that is within a second wavelength range different from the first range, wherein the second wavelength range comprises green light, red light, infrared (IR) light or blue light.

17. The method of claim 16, wherein the monitoring device is configured to be attached to the subject at one or more of the following body locations:

an ear, a limb, the nose, and a digit.

18. A method of generating data output containing physiological and motion-related information, the method comprising:

sensing physical activity and physiological information from a subject via a single monitoring device attached to the subject, wherein the monitoring device comprises at least one motion sensor for sensing the physical activity and at least one photoplethysmography (PPG) sensor for sensing the physiological information; and

processing signals from the at least one motion sensor and signals from the at least one PPG sensor via at least one processor, into a serial data output of physiological information and motion-related information,

wherein the serial data output is configured such that subject heart rate can be extracted from the physiological information, and such that a plurality of subject physical activity parameters can be extracted from the motion-related information, and such that data integrity can be extracted from the physiological information and/or the motion-related information.

19. A method of generating data output containing physiological information, the method comprising:

sensing physical activity and physiological information from a subject via a single monitoring device attached to the subject, wherein the monitoring device comprises a motion sensor and a photoplethysmography (PPG) sensor;

removing, via a first filter stage, one or more frequency bands from a PPG signal generated by the PPG sensor to produce a pre-conditioned PPG signal;

processing, via a second filter stage, the pre-conditioned PPG signal and a signal generated by the motion sensor to remove motion noise from the pre-conditioned PPG signal and produce a cleaner PPG signal; and

processing, via a third filter stage, the cleaner PPG signal to extract at least one physiological parameter.

20. The method of claim 19, wherein the first and third filter stages each comprise a plurality of digital filters.

21. The method of claim 19, wherein the second filter stage comprises an adaptive filter.

22. The method of claim 19, wherein the at least one physiological parameter comprises heart rate.

23. The method of claim 19, wherein the at least one physiological parameter comprises heart rate, and wherein a heart rate signal is extracted from PPG signal output from the third filter stage via a beat finding algorithm.

24. The method of claim 19, wherein the PPG sensor comprises at least one light guide configured to couple light to or from the body of a subject.

25. The method of claim 19, wherein the motion sensor comprises an accelerometer or an optical scatter detector.

26. The method of claim 19, wherein the motion sensor signal is further processed to generate a plurality of physical activity parameters.

27. The method of claim 19, wherein processing the cleaner PPG signal via the third filter stage comprises extracting a plurality of physiological parameters and producing a serial data output of the plurality of physiological parameters.

28. A method of generating data output containing physiological information, the method comprising:

sensing physical activity and physiological information from a subject via a single monitoring device attached to the subject, wherein the monitoring device comprises a motion sensor and a photoplethysmography (PPG) sensor;

processing, via a first filter stage, a PPG signal produced by the PPG sensor and a signal generated by the motion sensor to remove motion noise from the PPG signal and produce a cleaner PPG signal;

removing, via a second filter stage, one or more frequency bands from the cleaner PPG signal to produce a processed PPG signal; and

processing, via a third filter stage, the processed PPG signal to extract at least one physiological parameter.

29. The method of claim 28, wherein the second and third filter stages each comprise a plurality of digital filters.

30. The method of claim 28, wherein the first filter stage comprises an adaptive filter.

31. The method of claim 28, wherein the at least one physiological parameter comprises heart rate.

32. The method of claim 28, wherein the at least one physiological parameter comprises heart rate, and wherein a heart rate signal is extracted from PPG signal output from the third filter stage via a beat finding algorithm.

33. The method of claim 28, wherein the PPG sensor comprises at least one light guide configured to couple light to or from the body of a subject.

34. The method of claim 28, wherein the motion sensor comprises an accelerometer or an optical scatter detector.

35. The method of claim 28, wherein the motion sensor signal is further processed to generate a plurality of physical activity parameters.