QQ客服 官方微博 反馈留言

	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
会议日期	3-7 Dec. 2016
会议地点	Qingdao
国家	China
英文摘要	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.
内容类型	会议论文
源URL	[http://ir.ia.ac.cn/handle/173211/23129]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
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]. 见:. Qingdao. 3-7 Dec. 2016.

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。