System and method of biomechanical posture detection and feedback including sensor normalization

• US 9,936,900 B2
• Filed: 12/01/2016
• Issued: 04/10/2018
• Est. Priority Date: 07/13/2011
• Status: Active Grant

• Current Assignee: Seismic Holdings, Inc.
• Original Assignee: LUMO BodyTech, Inc.
• Inventors: Chang, Andrew Robert, Perkash, Monisha, Wang, C. Charles, Hauenstein, Andreas Martin
• Primary Examiner(s): MCNALLY, KERRI L
• Application Number:
  US15/366,429
• Publication Number:
  US 20170079562A1
• Time in Patent Office: 495 Days
• Field of Search: 3405737
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• 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 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/067 using accelerometers or gyroscopes
• 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 5/1116 Determining posture transitions
• CPC Class Codes: A61B 5/1121 Determining geometric values, e.g. centre of rotation or angular range of movement
• CPC Class Codes: A61B 5/4561 Evaluating static posture, e.g. undesirable back curvature A61B5/1116 takes precedence
• CPC Class Codes: A61B 5/486 Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: A61B 5/6823 Trunk, e.g., chest, back, abdomen, hip
• CPC Class Codes: G01P 15/00 Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
• CPC Class Codes: G06F 3/011 Arrangements for interaction with the human body, e.g. for user immersion in virtual reality blind teaching G09B21/00

Abstract

A system and method are described herein for a sensor device which biomechanically detects in real-time a user'"'"'s movement state and posture and then provides real-time feedback to the user based on the user'"'"'s real-time posture. The feedback is provided through immediate sensory feedback through the sensor device (e.g., a sound or vibration) as well as through an avatar within an associated application with which the sensor device communicates. The sensor device detects the user'"'"'s movement state and posture by capturing data from a tri-axial accelerometer in the sensor device. Streamed data from the accelerometer is normalized to correct for sensor errors as well as variations in sensor placement and orientation. Normalization is based on accelerometer data collected while the user is wearing the device and performing specific actions.

Claims

1. A method comprising:

capturing, by a tri-axial accelerometer attached to a user, first set of tri-axial accelerometer data over a first period of time while the user is in a first movement state;

averaging the captured first tri-axial accelerometer data and creating a first normalization matrix;

capturing, by the tri-axial accelerometer attached to the user, second set of tri-axial accelerometer data over a second period of time, while the user is in a second movement state;

averaging the captured second tri-axial accelerometer data and creating a second normalization matrix;

capturing, by the tri-axial accelerometer attached to the user, third tri-axial accelerometer data at a third point in time;

creating, by the microprocessor, normalized accelerometer data by applying the first normalization matrix and the second normalization matrix to the captured third tri-axial accelerometer data; and

analyzing at least the normalized accelerometer data and determining a current movement state by detecting at least one transition between two movement states.

2. The method of claim 1, further comprising determining a posture quality during the current movement state, which comprises determining an average pelvic tilt angle from the normalized accelerometer data.

3. The method of claim 2, wherein the posture quality is determined when the current movement state is a sitting movement state.

4. The method of claim 2, wherein the posture quality is determined when the current movement state is a standing movement state.

5. The method of claim 2, further comprising triggering feedback in response the posture quality.

6. The method of claim 1, wherein determining a current movement state by detecting at least one transition between two movement states comprises applying a rule-based model.

7. The method of claim 1, wherein determining a current movement state by detecting at least one transition between two movement states comprises applying a library comparison model and comparing the normalized accelerometer data to a movement library of movement state transition patterns.

8. The method of claim 1, wherein determining a current movement state by detecting at least one transition between two movement states comprises analyzing pelvic tilt angles as indicated in the normalized accelerometer data.

9. The method of claim 1, wherein determining a movement state comprises detecting at least one transition between any two of a set of the movement states including at least a standing movement state and a sitting movement state.

10. The method of claim 1, wherein determining a movement state comprises detecting at least one transition between any two of a set of the movement states including at least a walking movement state, a standing movement state, and a sitting movement state.

11. The method of claim 10, wherein the set of the movement states additionally comprises at least a running movement state and a lying movement state.

12. A postural feedback apparatus comprising:

a tri-axial accelerometer configured to be attached to a user, the tri-axial accelerometer configured to;

capture tri-axial accelerometer data over a first period of time while the user is in a first movement state,

capture a second set of tri-axial accelerometer data over a second period of time while the user is in a second movement state, and

capture real-time tri-axial accelerometer data over a third period of time;

a microprocessor configured to;

average the captured first tri-axial accelerometer data and create a first normalization matrix,

average the captured second tri-axial accelerometer data and create a second normalization matrix;

create normalized accelerometer data by applying the first normalization matrix and the second normalization matrix to the real-time tri-axial accelerometer data; and

analyze at least the normalized accelerometer data and determine a current movement state by detecting at least one transition between two movement states.

13. The apparatus of claim 12, wherein the microprocessor is further configured to determine a posture quality during the current movement state.

14. The apparatus of claim 13, wherein the posture quality is determined when the current movement state is a sitting movement state.

15. The apparatus of claim 13, wherein the microprocessor is further configured to trigger postural feedback based on the posture quality.

16. The apparatus of claim 12, wherein the configuration to determine a current movement state by detecting at least one transition between two movement states comprises configuration to apply a rule-based model.

17. The apparatus of claim 12, wherein the configuration to determine a current movement state by detecting at least one transition between two movement states comprises configuration to analyze pelvic-tilt angle as indicated in the normalized accelerometer data.

18. The apparatus of claim 12, wherein the configuration to determine a current movement state by detecting at least one transition between two movement states comprises configuration to compare the normalized accelerometer data to a movement library of movement state transition patterns.

19. The apparatus of claim 12, wherein configuration to determine a movement state comprises configuration to detect at least one transition between any two movement states from a set of the movement states including at least a standing movement state and a sitting movement state.

20. The apparatus of claim 12, wherein determining a movement state comprises configuration to detect at least one transition between any two movement states from a set of the movement states including at least a walking movement state, a standing movement state, a sitting movement state, a running state, and a lying state.