System and method of biomechanical posture detection and feedback including sensor normalization
First Claim
1. A method 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 walking;
averaging, by a microprocessor, the captured first tri-axial accelerometer data;
creating, by the microprocessor, a first normalization matrix for vertical alignment based on the averaged first tri-axial accelerometer data;
capturing, by the tri-axial accelerometer attached to the user, second tri-axial accelerometer data over a second period of time, while the user is stationary;
averaging, by the microprocessor, the captured second tri-axial accelerometer data;
creating, by the microprocessor, a second normalization matrix for lateral alignment based on an averaged third tri-axial accelerometer data;
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 movement and posture state of the user.
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Accused Products
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.
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Citations
23 Claims
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1. A method comprising:
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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 walking; averaging, by a microprocessor, the captured first tri-axial accelerometer data; creating, by the microprocessor, a first normalization matrix for vertical alignment based on the averaged first tri-axial accelerometer data; capturing, by the tri-axial accelerometer attached to the user, second tri-axial accelerometer data over a second period of time, while the user is stationary; averaging, by the microprocessor, the captured second tri-axial accelerometer data; creating, by the microprocessor, a second normalization matrix for lateral alignment based on an averaged third tri-axial accelerometer data; 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 movement and posture state of the user. - View Dependent Claims (2, 3, 4, 5, 6, 12, 13, 14, 15, 16)
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7. A postural feedback apparatus comprising:
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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 while the user is stationary, and capture third tri-axial accelerometer data at a third 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, average the captured second tri-axial accelerometer data; create a second normalization matrix based on the averaged captured second tri-axial accelerometer data; create normalized accelerometer data by applying the first normalization matrix and the second normalization matrix to the captured third tri-axial accelerometer data; and analyze at least the normalized accelerometer data and determining a movement and posture state of the user. - View Dependent Claims (8, 9, 10, 11)
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17. A method comprising:
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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 at a first point in time; averaging, by a microprocessor, the captured first tri-axial accelerometer data, wherein 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; 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; creating, by the microprocessor, first normalized accelerometer data by applying the first normalization matrix to the captured second tri-axial accelerometer data; recognizing, by the microprocessor, that the user is moving at a second point in time; 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; and analyzing at least the first normalized accelerometer data and determining a movement and posture state of the user. - View Dependent Claims (20, 21)
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18. A method comprising:
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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 at a first point in time; 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; creating, by the microprocessor, normalized accelerometer data by applying the first normalization matrix to the captured second tri-axial accelerometer data; 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 an averaged third tri-axial accelerometer data, and creating, by the microprocessor, second normalized accelerometer data by applying the second normalization matrix to the normalized accelerometer data; recognizing, by the microprocessor, that the user is moving at a second point in time; 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; and analyzing at least the first normalized accelerometer data and determining a movement and posture state of the user. - View Dependent Claims (19, 22, 23)
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Specification