Motion Recognition System Using Leg Angle Mapping for Personalized Assistance
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Solution Overview
Problem
Conventional motion assistance systems fail to provide effective assistance tailored to individual user movements, as they often offer standardized assistance regardless of the user's specific motion characteristics, leading to inefficient or inappropriate assistance.
Innovation Solution
A method and apparatus that map right and left leg angle information to context information, generate motion events based on preset criteria, and recognize user motions using a finite state machine (FSM) to provide personalized motion assistance, optimizing assistance by filtering out unnecessary support and adapting to the user's specific movements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional motion assistance apparatus provides set motion assistance regardless of user movements, then the apparatus structure remains simple, but the assistance effectiveness deteriorates
Solution Approach 1:
The motion recognition system segments the complex task of motion assistance into distinct functional modules: sensor unit for data collection, mapping unit for angle transformation, motion event generator for pattern recognition, and motion recognizer for state determination. This segmentation allows each module to handle specific aspects of motion analysis independently, improving overall system effectiveness while maintaining manageable complexity through modular architecture
Solution Approach 2:
The system dynamically adjusts motion assistance based on real-time recognition of user motion states. The motion recognizer continuously monitors motion events and transitions between different motion states (standing, walking, sitting, etc.), allowing the assistance apparatus to adapt its support characteristics to match the user's current activity level and motion requirements, thereby improving assistance effectiveness
2Adaptability or versatility
If the system provides motion assistance without recognizing specific motion types, then the system operation is simplified, but the adaptability to user characteristics deteriorates
Solution Approach 1:
The motion recognition system operates autonomously by automatically detecting, analyzing, and interpreting user motion characteristics without requiring external intervention. The sensor unit continuously monitors motion data, the mapping unit automatically transforms angles, the motion event generator independently identifies motion patterns, and the motion recognizer autonomously determines motion states, enabling the system to adapt to user characteristics self-service style
Solution Approach 2:
The system implements feedback mechanisms where the motion recognizer uses recognized motion states to adjust assistance parameters, which then feed back into the motion event generator for continuous refinement of motion detection. This feedback loop enables the system to adapt to user motion characteristics dynamically while maintaining straightforward operation through automated closed-loop control
3Measurement precision
If the system generates motion events without verifying duration, then the response speed increases, but the measurement precision deteriorates
Solution Approach 1:
The motion event generator performs preliminary filtering by verifying the duration of detected motion events against predefined thresholds before final recognition. This preliminary action eliminates spurious or transient motion detections, ensuring that only sustained and significant motion patterns are recognized, thereby improving measurement precision while the threshold-based approach maintains efficient processing time
Data Source
AI summary
A method and apparatus for recognizing a motion of a user are provided. The apparatus may map each of right leg angle information and left leg angle information to context information by comparing each of the right leg angle information and left leg angle information to a comparison value and/or preset threshold, may generate a motion event corresponding to the context information based on a criterion, and may recognize the motion of the user based on the motion event and a previous motion of the user.