Multi-Objective Optimization of a Lower Limb Prosthesis for Metabolically Efficient Walking Assistance

被引:1
作者
Li, Guoxin [1 ,2 ]
Wang, Jiandong [3 ]
Li, Zhijun [1 ,2 ]
Yen, Gary G. [4 ]
Qi, Qi [5 ,6 ]
Xing, Jinqiu [7 ]
机构
[1] Tongji Univ, Shanghai Yangzhi Rehabil Hosp, Shanghai Sunshine Rehabil Ctr, Sch Mech Engn, Shanghai 201804, Peoples R China
[2] Tongji Univ, Shanghai Yangzhi Rehabil Hosp, Translat Res Ctr, Shanghai Sunshine Rehabil Ctr, Shanghai 201804, Peoples R China
[3] Univ Sci & Technol China, Inst Adv Technol, Hefei 230031, Peoples R China
[4] Oklahoma State Univ, Sch Elect & Comp Engn, Stillwater, OK 74078 USA
[5] Tongji Univ, Shanghai Yangzhi Rehabil Hosp, Shanghai Sunshine Rehabil Ctr, Shanghai 201804, Peoples R China
[6] Tongji Univ, Dept Rehabil, Shanghai 201804, Peoples R China
[7] Guangzhou Yikang Med Equipment Ind Co Ltd, Guangzhou 511447, Peoples R China
关键词
Prosthetics; Legged locomotion; Optimization; Motors; Costs; Robots; Muscles; Multi-objective optimization; knee-guided evolutionary algorithm; lower limb prosthesis; metabolically efficient walking; ENERGY-EXPENDITURE; MUSCLE; MODEL; KNEE; DESIGN; ANKLE; COST; EMG;
D O I
10.1109/TASE.2024.3370615
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Enhancing energy efficiency is pivotal for advancing robotic lower limb prostheses. However, the conventional control strategy in powered prostheses displays notable variance in energy economy across terrains during walking. This challenge could be managed by developing control optimization methods to effectively reduce the subject's metabolic cost and the device's energy expenditure, thereby improving the walking economy in diverse environments. In this study, we investigate a multi-objective optimization problem (MOP) for controlling above-knee prostheses, intending to reduce prosthetic power consumption and the subject's metabolic costs during walking activities. To bolster real-time performance in the optimization loop, we introduce a knee-guided evolutionary algorithm (KGEA) for MOP, which efficiently reduces exploration space and time complexity, thus enabling the practical implementation of a limited number of solutions in each iteration. The effectiveness of the proposed optimization-based strategy was evaluated through experiments involving two lower limb amputees engaging in slope, stair, and flat walking. Our results demonstrated that the optimization-based strategy significantly reduced the subjects' metabolic consumption, with an average reduction of 16.53% for subject 1 and 10.23% for subject 2 across different terrains, compared to using the prosthesis without the optimization strategy. This promising outcome marks a substantial advancement in the development of energy-efficient, multi-degree-of-freedom power prostheses.
引用
收藏
页码:4606 / 4621
页数:16
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