Intelligent Knee Prostheses: A Systematic Review of Control Strategies

被引:8
|
作者
Li, Linrong [1 ,2 ,3 ]
Wang, Xiaoming [1 ,2 ,3 ]
Meng, Qiaoling [1 ,2 ,3 ]
Chen, Changlong [1 ,2 ,3 ]
Sun, Jie [1 ,2 ,3 ]
Yu, Hongliu [1 ,2 ,3 ]
机构
[1] Univ Shanghai Sci & Technol, Inst Rehabil Engn & Technol, 516 Jungong Rd, Shanghai 200093, Peoples R China
[2] Shanghai Engn Res Ctr Assist Devices, Shanghai 200093, Peoples R China
[3] Minist Civil Affairs, Key Lab Neural Funct Informat & Rehabil Engn, Shanghai 200093, Peoples R China
基金
中国国家自然科学基金;
关键词
Intelligent knee prosthesis; Finite-state machine; Volitional control; Sensor system; Intent recognition; Parameter tuning; VIRTUAL CONSTRAINT CONTROL; POWERED KNEE; INTENT RECOGNITION; TRANSFEMORAL-PROSTHESIS; IMPEDANCE CONTROL; ANKLE PROSTHESIS; VOLITIONAL CONTROL; CONTROL SCHEME; DESIGN; AMPUTEE;
D O I
10.1007/s42235-022-00169-1
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The intelligent knee prosthesis is capable of human-like bionic lower limb control through advanced control systems and artificial intelligence algorithms that will potentially minimize gait limitations for above-knee amputees and facilitate their reintegration into society. In this paper, we sum up the control strategies corresponding to the prevailing control objectives (position and impedance) of the current intelligent knee prosthesis. Although these control strategies have been successfully implemented and validated in relevant experiments, the existing deficiencies still fail to achieve optimal performance of the controllers, which complicates the definition of a standard control method. Before a mature control system can be developed, it is more important to realize the full potential for the control strategy, which requires upgrading and refining the relevant key technologies based on the existing control methods. For this reason, we discuss potential areas for improvement of the prosthetic control system based on the summarized control strategies, including intent recognition, sensor system, prosthetic evaluation, and parameter optimization algorithms, providing future directions toward optimizing control strategies for the next generation of intelligent knee prostheses.
引用
收藏
页码:1242 / 1260
页数:19
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