Wearable Posture Recognition Error Compensation
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Solution Overview
Problem
Posture recognition systems using clothing-type sensors face limitations due to errors caused by sensor position changes, such as slipping, which are not adequately addressed by existing technologies, especially when the user's motion changes the error's cause and magnitude.
Innovation Solution
A posture recognition system that includes a posture estimation section and an error estimation section, using sensor data from wearable sensors attached to clothing to calculate posture data and error data, allowing for real-time error classification and response to changing motion-induced errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If sensors are attached to clothing for posture recognition, then limitations on user action are reduced, but errors occur due to sensor position changes from clothing slipping
Solution Approach 1:
The system pre-calculates error characteristics for multiple possible user motions before actual posture recognition occurs. By preparing error data in advance for various motion types, the system can quickly compensate for position changes without delaying the recognition process, thus maintaining both user freedom and measurement precision.
Solution Approach 2:
The system uses detected user motion information as feedback to select appropriate error characteristics from pre-calculated data. This feedback mechanism allows the system to adapt to actual user movements and apply the correct error compensation, resolving the contradiction between clothing mobility and measurement accuracy.
2Measurement precision
If multiple sensors are arranged in proximity to handle position changes, then some errors are reduced, but it is difficult to respond to errors whose cause and magnitude change according to user motion
Solution Approach 1:
The system dynamically selects error characteristics based on the detected user motion type. Instead of using fixed error compensation, the system adapts the error model to match the actual motion being performed, enabling accurate response to errors whose magnitude and cause vary with user motion.
Solution Approach 2:
The system changes the error compensation parameters according to the detected motion type. By storing multiple sets of error characteristics corresponding to different motions and selecting the appropriate set based on current motion, the system can accurately compensate for position changes regardless of the specific motion being performed.
3Measurement precision
If error compensation is applied for specific motions, then accuracy is improved for those motions, but errors from other motion types are not properly addressed
Solution Approach 1:
The system creates a universal error compensation mechanism that handles multiple motion types through a single integrated approach. By pre-calculating error characteristics for various motions and selecting the appropriate ones based on detected motion, the system achieves broad coverage across different user actions while maintaining accuracy for each specific motion type.
Data Source
AI summary
Provided is a posture recognition system that can properly respond to an error that is changed according to a user's motion. A posture estimation section calculates posture data indicating a posture of a user wearing clothing, on the basis of motion data measured by a posture sensor attached to the clothing. An error estimation section calculates error data which is an estimate of an error that is occurring in the posture data, on the basis of the motion data and the posture data.