Noninvasive Human-Prosthesis Interfaces for Locomotion Intent Recognition: A Review
Author(s) -
Dongfang Xu,
Qining Wang
Publication year - 2021
Publication title -
cyborg and bionic systems
Language(s) - English
Resource type - Journals
eISSN - 2097-1087
pISSN - 2692-7632
DOI - 10.34133/2021/9863761
Subject(s) - prosthesis , computer science , human–computer interaction , task (project management) , gait , event (particle physics) , scope (computer science) , artificial intelligence , physical medicine and rehabilitation , engineering , medicine , physics , systems engineering , quantum mechanics , programming language
The lower-limb robotic prostheses can provide assistance for amputees’ daily activities by restoring the biomechanical functions of missing limb(s). To set proper control strategies and develop the corresponding controller for robotic prosthesis, a prosthesis user’s intent must be acquired in time, which is still a major challenge and has attracted intensive attentions. This work focuses on the robotic prosthesis user’s locomotion intent recognition based on the noninvasive sensing methods from the recognition task perspective (locomotion mode recognition, gait event detection, and continuous gait phase estimation) and reviews the state-of-the-art intent recognition techniques in a lower-limb prosthesis scope. The current research status, including recognition approach, progress, challenges, and future prospects in the human’s intent recognition, has been reviewed. In particular for the recognition approach, the paper analyzes the recent studies and discusses the role of each element in locomotion intent recognition. This work summarizes the existing research results and problems and contributes a general framework for the intent recognition based on lower-limb prosthesis.
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