System and Method of Biomechanical Posture Detection and Feedback Including Sensor Normalization

• US 20150335280A1
• Filed: 07/31/2015
• Published: 11/26/2015
• 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
• Granted Patent: US 9,541,994 B2
• 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 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 of normalizing accelerometer data comprising:

capturing, by a tri-axial accelerometer attached to a user, first tri-axial accelerometer data over a first period of time while the user is moving as instructed;

averaging, by a microprocessor, the captured first tri-axial accelerometer data;

creating, by the microprocessor, a first normalization matrix based on the averaged first tri-axial accelerometer data;

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

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

2. The method of claim 1 further comprising, before averaging by the microprocessor the captured first tri-axial accelerometer data:

calculating, by the microprocessor, smoothed power from the captured first tri-axial accelerometer data;

identifying, by the microprocessor, data in the captured first tri-axial accelerometer data which results in the calculated power being below a threshold; and

discarding, by the microprocessor, the identified data from the captured first tri-axial accelerometer data.

3. The method of claim 1 further comprising, after creating by the microprocessor the first normalized accelerometer data:

capturing, by the tri-axial accelerometer attached to the user, third tri-axial accelerometer data over a third period of time, while the user is stationary as instructed;

averaging, by the microprocessor, the captured third tri-axial accelerometer data;

creating, by the microprocessor, a second normalization matrix based on the averaged third tri-axial accelerometer data; and

creating, by the microprocessor, second normalized accelerometer data by applying the second normalization matrix to the first normalized accelerometer data.

4. The method of claim 1 further comprising, after creating by the microprocessor the first normalized accelerometer data:

recognizing, by the microprocessor, that the user is moving;

averaging, by the microprocessor, the first normalized accelerometer data;

calculating, by the microprocessor, a shift angle from the averaged first normalized accelerometer data; and

adjusting, by the microprocessor, the first normalized accelerometer data based on the calculated shift angle.

5. The method of claim 4 where recognizing by the microprocessor that the user is moving comprises comparing a smoothed power calculated from the first normalized accelerometer data to a threshold.

6. The method of claim 1 where the tri-axial accelerometer is attached to the user on the user'"'"'s trunk, head, neck, or a limb.

7. The method of claim 1 further comprising, after creating by the microprocessor the first normalized accelerometer data:

recognizing, by the microprocessor, that the first normalized accelerometer data indicates the tri-axial accelerometer is upside-down; and

correcting, by the microprocessor, the first normalized accelerometer data to account for the indication the tri-axial accelerometer is upside-down.

8. method of claim 1 where moving as instructed comprises walking.

9. The method of claim 3 where stationary as instructed comprises sitting and leaning back.

10. A postural feedback apparatus comprising:

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

capture first tri-axial accelerometer data over a first period of time while the user is moving as instructed,

capture second tri-axial accelerometer data at a second point in time; and

a microprocessor configured to;

average the captured first tri-axial accelerometer data,

create a first normalization matrix based on the averaged captured first tri-axial accelerometer data, and

create first normalized accelerometer data by applying the first normalization matrix to the captured second tri-axial accelerometer data.

11. The apparatus of claim 10 where the microprocessor is further configured to:

calculate a smoothed power from the captured first tri-axial accelerometer data,

identify data in the captured first tri-axial accelerometer data which results in the calculated smoothed power being below a threshold; and

discard the identified data from the captured first tri-axial accelerometer data, prior to averaging the captured first tri-axial accelerometer data.

12. The apparatus of claim 10 where

the tri-axial accelerometer is further configured to capture third tri-axial accelerometer data over a third period of time while the user is stationary as instructed;

and

the microprocessor is further configured to;

average the captured third tri-axial accelerometer data;

create a second normalization matrix based on the averaged captured third tri-axial accelerometer data; and

create second normalized accelerometer data by applying the second normalization matrix to the first normalized accelerometer data.

13. The apparatus of claim 10 where the microprocessor is further configured to:

recognize that the user is moving based on the first normalized accelerometer data;

average the first normalized accelerometer data;

calculate a shift angle from the averaged first normalized accelerometer data; and

adjust the first normalized accelerometer data based on the calculated shift angle.

14. The apparatus of claim 10 where the tri-axial accelerometer is attached to the user on the user'"'"'s trunk, head, neck, or a limb.

15. The apparatus of claim 10 where moving as instructed comprises walking.

16. apparatus of claim 12 where stationary as instructed comprises sitting and leaning back.

17. The apparatus of claim 10 where the microprocessor is further configured to:

recognize that the first normalized accelerometer data indicates the tri-axial accelerometer is upside-down; and

correct the first normalized accelerometer data to account for the indication that the tri-axial accelerometer is upside-down.

18. A non-transitory computer readable medium having stored thereupon computing instructions comprising:

a code segment to capture first tri-axial accelerometer data over a first period of time while the user is moving as instructed;

a code segment to average the captured first tri-axial accelerometer data;

a code segment to create a first normalization matrix based on the averaged first tri-axial accelerometer data;

a code segment to capture second tri-axial accelerometer data at a second point in time; and

a code segment to create first normalized accelerometer data by applying the first normalization matrix to the captured second tri-axial accelerometer data.

19. The non-transitory computer readable medium of claim 18 having stored thereupon computing instructions comprising:

a code segment to calculate smoothed power from the captured first tri-axial accelerometer data;

a code segment to identify data in the captured first tri-axial accelerometer data which results in the calculated power being below a threshold; and

a code segment to discard the identified data from the captured first tri-axial accelerometer data, prior to averaging by the microprocessor the captured first tri-axial accelerometer data.

20. The non-transitory computer readable medium of claim 18 having stored thereupon computing instructions further comprising:

a code segment to capture third tri-axial accelerometer data over a third period of time, while the user is stationary as instructed;

a code segment to average the captured third tri-axial accelerometer data;

a code segment to create a second normalization matrix based on the averaged third tri-axial accelerometer data; and

a code segment to create second normalized accelerometer data by applying the second normalization matrix to the first normalized accelerometer data.

21. The non-transitory computer readable medium of claim 18 having stored thereupon computing instructions further comprising:

a code segment to recognize that the user is moving by comparing a smoothed power calculated from the first normalized accelerometer data to a threshold;

a code segment to average the first normalized accelerometer data;

a code segment to calculate a shift angle from the averaged first normalized accelerometer data; and

a code segment to adjust the first normalized accelerometer data based on the calculated shift angle.

22. The non-transitory computer readable medium of claim 18 having stored thereupon computing instructions further comprising:

a code segment to recognize that the first normalized accelerometer data indicates the tri-axial accelerometer is upside-down; and

a code segment to correct the first normalized accelerometer data to account for the indication the tri-axial accelerometer is upside-down.