An sEMG-driven neuromuskeloskeletal model of upper limb for rehabilitation robot control
Liang Peng; Zeng-Guang Hou; Lincong Luo; Long Peng; Weiqun Wang; Long Cheng
2016
会议名称2016 IEEE International Conference on Robotics and Biomimetics (ROBIO)
会议日期3-7 Dec. 2016
会议地点Qingdao
会议举办国China
摘要This study proposes a new method for modeling the complicated dynamics between motor neural signal (surface electromyography, sEMG) and corresponding joint torque of muscle contraction (sEMG-driven neuromusculoskeletal model), which has potential to be used for rehabilitation robot control and neuromuscular evaluation after stroke, etc. In this model, muscle activation dynamics and contraction dynamics are built based on Hill-type muscle model, which has many parameters to be determined using optimization methods, and training samples of sEMG, joint angles, and joint torques are acquired with the aid of an upper-limb rehabilitation robot. Subject-specific parameters are initialized with scaled Standford VA model data by subjects' weight, limb length, etc., and the model is optimized using the genetic algorithm (GA). Based on this study, characteristics of a certain single muscle during voluntary movements can be obtained by measuring their sEMG signals, and the motor commands of brain are decoded in some degree.
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/23129
专题复杂系统管理与控制国家重点实验室_先进机器人
推荐引用方式
GB/T 7714
Liang Peng,Zeng-Guang Hou,Lincong Luo,et al. An sEMG-driven neuromuskeloskeletal model of upper limb for rehabilitation robot control[C],2016.
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