Exosuit Posture Session Segmentation for Biomechanical Feedback
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Solution Overview
Problem
Current wearable robotic systems lack effective methods for monitoring and providing feedback on user posture, leading to inefficient data analysis and inadequate assistance during activities.
Innovation Solution
An exosuit system with a base layer, power layer, and sensors that analyze user movement data to identify posture sessions and provide feedback, incorporating inertial sensors like accelerometers, gyroscopes, and magnetometers to segment and analyze posture data for smarter feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous posture monitoring is performed throughout the entire exosuit use period, then complete posture data is collected, but data analysis becomes inefficient and feedback is delayed
Solution Approach 1:
The patent segments continuous posture monitoring data into discrete posture sessions based on activity transitions detected by sensors. High-activity segments (when the user is moving or performing tasks) are identified and excluded from detailed posture analysis, while low-activity segments (rest periods between tasks) are selected for posture monitoring. This segmentation approach maintains complete monitoring coverage while significantly reducing the volume of data requiring detailed analysis, thereby improving processing efficiency without sacrificing monitoring completeness.
2Loss of information
If posture data from all activity segments is analyzed, then comprehensive feedback is provided, but processing time and computational resources increase
Solution Approach 1:
The patent extracts and excludes high-activity segments from detailed posture analysis by identifying activity transitions through sensor data. During high-activity periods when the user is moving or performing tasks, posture monitoring continues but detailed analysis is suspended. Only during low-activity segments (rest periods) is comprehensive posture analysis performed. This extraction approach ensures that feedback remains comprehensive for relevant periods while eliminating unnecessary processing during active tasks, thus reducing overall processing time without losing critical posture information.
3Measurement precision
If posture feedback is provided continuously, then user awareness is maximized, but user comfort decreases due to constant interruptions
Solution Approach 1:
The patent implements periodic posture feedback by providing corrections only during low-activity segments rather than continuously. The system monitors posture throughout the entire exosuit use period but delivers feedback interruptions only when the user is at rest between tasks. This periodic feedback approach maintains accurate posture monitoring and correction capabilities while significantly reducing the frequency of user interruptions, thereby improving user comfort and acceptance without sacrificing feedback accuracy when delivered.
4Reliability
If all sensor data is processed without segmentation, then no posture sessions are missed, but energy consumption increases
Solution Approach 1:
The patent segments sensor data processing into two distinct modes: continuous light monitoring during all periods to detect activity transitions, and intensive posture analysis only during low-activity segments. The system maintains reliable posture session detection by continuously monitoring for activity transitions that mark session boundaries, but processes detailed posture data only during rest periods. This segmentation approach ensures no posture sessions are missed while dramatically reducing the computational energy required for processing, as the intensive analysis is performed only when the user is not actively moving or working.
Data Source
AI summary
Systems and methods for monitoring posture of a user wearing an exosuit are discussed herein. Exosuits worn by users can monitor several movement factors that characterize the user's movements and posture. The user's posture is identified and analyzed, and feedback is provided to the user based on the analyzed posture.