Walking Assistance Apparatus Gait Task Recognition
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Solution Overview
Problem
Existing walking assistance apparatuses lack effective methods to recognize and adapt to various gait tasks, particularly for users with joint issues, limiting their ability to provide personalized and efficient support during different walking motions.
Innovation Solution
A method and apparatus that determine whether a user's foot is in contact with the ground by analyzing joint motion information, including hip, knee, and ankle angles, and acceleration, to classify gait tasks such as ascending, descending, or parallel motions, and adjust the assistance accordingly, using a combination of sensors and machine learning-based recognizers to generate control information for the walking assistance apparatus.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If walking assistance apparatuses use general control methods, then device complexity is reduced, but adaptability to different gait tasks deteriorates
Solution Approach 1:
The gait task recognition is divided into multiple stages: first determining whether the foot is in contact with the ground, then determining a first gait task based on joint motion information at contact points, and finally determining a second gait task based on additional joint motion information. This segmented approach allows the system to handle different gait tasks adaptively without requiring a single complex control algorithm to cover all possibilities.
Solution Approach 2:
The system performs preliminary determination of foot-ground contact status before determining the specific gait task. By pre-identifying contact points in time and establishing the basic walking state first, the system prepares the foundation for subsequent gait task classification, enabling adaptive control without overwhelming complexity.
2Measurement precision
If the apparatus measures detailed joint motion information, then measurement precision improves, but device complexity increases
Solution Approach 1:
The system applies different measurement requirements to different locations and phases of the gait cycle. Joint motion information is measured at specific contact points in time rather than continuously, and different types of joint motion data (hip, knee, ankle angles) are collected selectively based on the gait phase. This localized measurement approach achieves high precision where needed while avoiding unnecessary measurements elsewhere.
Solution Approach 2:
The walking assistance apparatus uses the user's own joint motion information to determine gait tasks and control assistance. The system leverages the natural motion data generated by the user's walking, converting this self-produced information into control signals without requiring external measurement equipment or additional sensors.
3Adaptability or versatility
If the system determines multiple gait tasks sequentially, then adaptability to specific gait phases improves, but loss of time in processing increases
Solution Approach 1:
The system determines gait tasks at periodic intervals based on foot-ground contact events. Rather than continuously analyzing all possible gait parameters, the system triggers gait task determination at specific periodic moments (contact points), which naturally segment the gait cycle into manageable analysis intervals. This periodic approach maintains high recognition accuracy while minimizing unnecessary processing during transition phases.
Data Source
AI summary
Walking assistance apparatuses and methods of controlling the walking assistance apparatus are provided. The walking assistance apparatus may recognize a type of a gait task of a user, and may assist a gait of the user to be suitable for the recognized gait task. The walking assistance apparatus may recognize the gait task as various categories using a pre-trained recognizer.