Noninvasive Human-Prosthesis Interfaces for Locomotion Intent Recognition: A Review.

Dongfang Xu,Qining Wang

doi:10.34133/2021/9863761

Abstract

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.

Highlights

Lower-limb robotic prostheses, mainly including knee-ankle and ankle-foot prostheses, have achieved a fast development within these years, since it can provide the functional compensation for amputees by mimicking the biomechanical features of joints [1,2,3,4,5]
The kinematics and dynamics of different joints vary a lot in these locomotion modes, and the prostheses need to mimic the biomechanics of missing joints
They have conducted a preliminary study with an adaptive recognition system for novel users using a powered lower-limb prosthesis and achieved good effects: compared to a nonadaptive system, the adaptive system can reduce the number of errors by 32.9% [104]

Summary

Introduction

Lower-limb robotic prostheses, mainly including knee-ankle and ankle-foot prostheses, have achieved a fast development within these years, since it can provide the functional compensation for amputees by mimicking the biomechanical features of joints [1,2,3,4,5]. Some lower-limb’s movements can be viewed as periodical or quasi-periodical in structured environment, and these common periodical activities include level ground walking (LG), stair ascending (SA), stair descending (SD), ramp ascending (RA), and ramp descending (RD). Apart from these periodical movements, there are some nonperiodical movements, such as sitting, standing, stepping over an obstacle, turning around, and walking on uneven terrains or between different terrains. The most used finite-state machine control method for robotic prostheses is based on these states (detected gait phase and events) [6, 7], as the set function of prosthesis in each state is different. In addition to the finite-state machine control method, some alternatives are developed based on the estimation of the continuous gait phase that increases monotonically in each gait cycle

Methods

Findings

Discussion

Conclusion