sEMG-based continuous estimation of joint angles of human legs by using BP neural network
sEMG-based continuous estimation of joint angles of human legs by using BP neural network
复制标题
基于sEMG的BP神经网络连续估计人体腿部关节角度
DOI：
10.1016/j.neucom.2011.05.033
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发表时间：
2012-02-15
期刊：
影响因子：
6
通讯作者：
Tan, Min
中科院分区：
文献类型：
--
作者：
Zhang, Feng;Li, Pengfeng;Tan, Min
本文提出了一种描述人腿关节角度与表面肌电信号关系的m阶非线性模型，并利用简单的BP神经网络对模型进行估计。模型的输入是经过处理的肌电信号时间序列，模型的输出是髋关节、膝关节和踝关节的关节角度。为了验证BP神经网络的有效性，6名健全人和4名脊髓损伤患者参与了实验。健全人分别进行不同速度、不同负荷下的跑步机运动和伸腿运动两种运动模式，SCI患者只选择跑步机运动。记录人体7块腿部肌肉的7条肌电信号通道，同时采集髋关节、膝关节、踝关节3个关节角度。结果表明，该方法对健全人和脊髓损伤患者的关节角估计都有较好的效果。所有健全人伸腿运动的平均角度估计均方根误差小于9度，跑步机运动的平均均方根误差小于6度。脊髓损伤患者由于运动范围更小，其平均角度估计均方根误差比健全人更小（小于5度）。该方法将用于康复机器人或功能性电刺激（FES）基于表面肌电信号对SCI患者或脑卒中患者进行主动康复。(C) 2011 Elsevier B.V.版权所有
In this paper, we propose an mth order nonlinear model to describe the relationship between the surface electromyography (sEMG) signals and the joint angles of human legs, in which a simple BP neural network is built for the model estimation. The inputs of the model are sEMG time series that have been processed, and the outputs of the model are the joint angles of hip, knee, and ankle. To validate the effectiveness of the BP neural network, six able-bodied people and four spinal cord injury (SCI) patients participated in the experiment. Two movement modes including the treadmill exercise and the leg extension exercise at different speeds and different loads were respectively conducted by the able-bodied individuals, and only the treadmill exercise was selected for the SCI patients. Seven channels of sEMG from seven human leg muscles were recorded and three joint angles including the hip joint, knee joint and the ankle joint were sampled simultaneously. The results present that this method has a good performance on joint angles estimation by using sEMG for both able-bodied subjects and SCI patients. The average angle estimation root-mean-square (rms) error for leg extension exercise is less than 9 degrees, and the average rms error for treadmill exercise is less than 6 degrees for all the able-bodied subjects. The average angle estimation rms error of the SCI patients is even smaller (less than 5 degrees) than that of the able-bodied people because of a smaller movement range. This method would be used to rehabilitation robot or functional electrical stimulation (FES) for active rehabilitation of SCI patients or stroke patients based on sEMG signals. (C) 2011 Elsevier B.V. All rights reserved.