DETERMINING PHYSIOLOGICAL CHARACTERISTICS FROM SENSOR SIGNALS INCLUDING MOTION ARTIFACTS

• US 20150230756A1
• Filed: 03/13/2013
• Published: 08/20/2015
• Est. Priority Date: 09/29/2012
• Status: Abandoned Application

• Current Assignee: JB IP Acquisitions LLC
• Original Assignee: AliphCom, Inc. (AliphCom Corp.)
• Inventors: Luna, Michael Edward Smith, Saha, Sankalita, Fullam, Scott
• Application Number:
  US13/802,305
• Publication Number:
  US 20150230756A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 2562/043 in a linear array
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• 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 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• 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 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/02444 Details of sensor A61B5/02427 takes precedence
• CPC Class Codes: A61B 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• CPC Class Codes: A61B 5/053 Measuring electrical impedance or conductance of a portion of the body
• CPC Class Codes: A61B 5/0531 Measuring skin impedance
• CPC Class Codes: A61B 5/08 Detecting, measuring or recording devices for evaluating the respiratory organs A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/0809 by impedance pneumography
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/1101 Detecting tremor
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/24 Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
• CPC Class Codes: A61B 5/4812 Detecting sleep stages or cycles
• CPC Class Codes: A61B 5/4866 Evaluating metabolism A61B5/083 takes precedence
• CPC Class Codes: A61B 5/681 : Wristwatch-type devices
• CPC Class Codes: A61B 5/6824 : Arm or wrist
• CPC Class Codes: A61B 5/6831 : Straps, bands or harnesses
• 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 5/7246 : using correlation, e.g. template matching or determination of similarity
• 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: A61M 2021/0083 : especially for waking up
• CPC Class Codes: A61M 21/00 : Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis

Abstract

Embodiments relate generally to electrical and electronic hardware, computer software, wired and wireless network communications, and wearable computing devices in capturing and deriving physiological characteristic data. More specifically, disclosed are one or more electrodes and methods to determine physiological characteristics using a wearable device (or carried device) and one or more sensors that can be subject to motion. In one embodiment, a method includes receiving a sensor signal during one or more portions of a time interval in which the wearable device is in motion, and receiving a motion sensor signal. The method includes decomposing at a processor the sensor signal to determine physiological signal components. An analysis of the physiological signal components can yield a physiological characteristic, whereby a physiological characteristic signal that includes data representing the physiological characteristic can be generated during at least one of the one or more portions of the time interval.

Claims

1. A method comprising:

receiving a sensor signal including data representing physiological characteristics in a wearable device during one or more portions of a time interval in which the wearable device is in motion;

receiving a motion sensor signal;

decomposing at a processor the sensor signal to determine physiological signal components and motion signal components based on the sensor signal and the motion sensor signal;

analyzing the physiological signal components to determine a physiological characteristic; and

generating a physiological characteristic signal that includes data representing the physiological characteristic during at least one of the one or more portions of the time interval.

2. The method of claim 1, wherein receiving the sensor signal comprises:

receiving the sensor signal at a distal end of a limb at which the wearable device is disposed.

3. The method of claim 1, wherein receiving the sensor signal comprises:

receiving a bio-impedance signal at a distal end of a limb at which the wearable device is disposed.

4. The method of claim 1, wherein generating the physiological characteristic signal that includes the data representing the physiological characteristic comprises:

generating the physiological characteristic signal that includes the data representing one or more of a heart rate, a respiration rate, and a Mayer wave rate.

5. The method of claim 1, wherein decomposing the sensor signal comprises:

correlating data representing the motion sensor signal to data representing the sensor signal.

6. The method of claim 5, wherein correlating the data representing the motion sensor signal comprises:

scaling the data representing the motion sensor signal to equivalent values of the data representing the sensor signal.

7. The method of claim 1, wherein decomposing the sensor signal comprises:

forming a matrix including coefficients configured to attenuate values of the physiological signal components for the motion sensor signal.

8. The method of claim 7, wherein forming the matrix comprises:

forming a mixing matrix.

9. The method of claim 7, further comprising:

inverting the matrix.

10. The method of claim 9, wherein inverting the matrix comprises:

forming an inverted mixing matrix.

11. The method of claim 1, wherein decomposing the sensor signal comprises:

applying an inverted matrix to samples of the physiological signal components and the motion signal components; and

recovering data representing the physiological characteristic signal.

12. The method of claim 1, further comprising:

determining an amount of motion associated with the motion sensor signal; and

adjusting a dynamic range of operation of an amplifier configured to receive the sensor signal responsive to the amount of motion.

13. The method of claim 12, further comprising:

determining the amount of motion is associated with a threshold range of values of motion; and

applying an offset value to the amplifier to modify a range of output values of the amplifier.

14. The method of claim 1, further comprising:

preprocessing the sensor signal to reduce one or more portions of noise.

15. The method of claim 1, wherein receiving the motion sensor signal comprises:

receiving a plurality of data streams representing accelerometer data in a plurality of axes;

determining a data stream associated with an axis in which the magnitude of acceleration of the motion is the greatest; and

selecting the data stream as the motion sensor signal.

16. An apparatus comprising:

a wearable housing;

a motion sensor configured to sense motion associated with the wearable housing and to generate a motion sensor signal;

one or more electrodes disposed in the wearable housing configured to receive a sensor signal including data representing one or more physiological characteristics during one or more portions of a time interval in which the wearable device is in motion; and

a processor configured to execute instructions to implement a motion artifact reduction unit that is configured to;

extract from the sensor signal, which includes a signal component associated with motion artifacts, to determine a physiological signal based on the sensor signal and the motion sensor signal; and

generate a physiological characteristic signal that includes data representing the physiological characteristic during at least one of the one or more portions of the time interval.

17. The apparatus of claim 16, wherein the wearable housing is configured to couple to a portion of a limb at its distal end.

18. The apparatus of claim 16, further comprising:

a stream selector configured to select a subset of the motion associated with an axis having a greatest amount of motion,

wherein the processor is further configured to;

correlate data representing the subset of the motion to the sensor signal;

apply an inverted mixing matrix of coefficients to samples of the sensor signal;

recover the physiological characteristic signal.

19. The apparatus of claim 18, wherein the physiological characteristic signal comprises:

data representing one or more of a heart rate, a respiration rate, and a Mayer wave rate.

20. The apparatus of claim 16, wherein the processor further configured to execute instructions to implement an offset generator that is configured to:

determine an amount of motion associated with the motion sensor signal; and

adjust a dynamic range of operation of an amplifier configured to receive the sensor signal responsive to the amount of motion.