Intelligent Knee Prostheses: A Systematic Review of Control Strategies
作者机构：Institute of Rehabilitation Engineering and TechnologyUniversity of Shanghai for Science and TechnologyNo.516Jungong RoadYangpu DistrictShanghai 200093China Shanghai Engineering Research Center of Assistive DevicesShanghai 200093China Key Laboratory of Neural-Functional Information and Rehabilitation Engineering of the Ministry of Civil AffairsShanghai 200093China
出 版 物：《Journal of Bionic Engineering》 (仿生工程学报（英文版）)
年 卷 期：2022年第19卷第5期
页 面：1242-1260页
核心收录：
学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：The authors would liketo thank the support of the National Natural Science Foundation of China(grant no.62073224) National Key Research and Development Program of China(grant no.2018YFB1307303)
主 题：Intelligent knee prosthesis Finite-state machine Volitional control Sensor system Intent recognition Parameter tuning
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 *** this paper,we sum up the control strategies corresponding to the prevailing control objectives(position and impedance)of the current intelligent knee *** 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 *** 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 *** 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.
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