Prediction of EMG signals of trunk muscles in manual lifting using a neural network model
Prediction of EMG signals of trunk muscles in manual lifting using a neural network model
复制标题
使用神经网络模型预测手动举重时躯干肌肉的肌电信号
DOI：
10.1109/ijcnn.2004.1380908
复制
发表时间：
2004
期刊：
影响因子：
--
通讯作者：
W. Karwowski
中科院分区：
文献类型：
--
作者：
Y. Hou;J. Zurada;W. Karwowski
利用人工神经网络建立了肌电信号的预测模型。选择运动学变量和被试变量作为模型的输入。为了获得更好的预测精度，本文提出了一种新的前馈神经网络结构。通过在输入和输出之间增加区域连接，新的神经网络结构可以同时具有从输入提取的全局特征和区域特征。全球连接更注重全局，决定预测曲线的全球趋势，而区域连接则集中在每个点，局部修正预测。在建模中采用了反向传播算法。讨论了针对这一问题设计的神经网络的基本结构。然后，为了克服其缺点，我们提出了一种新的结构。
An EMG (electromyography) signal prediction model is built using artificial neural network. Kinematics variables and subject variables are selected as inputs of this model. A novel structure of feedforward neural network is proposed in This work to obtain better accuracy of prediction. By adding regional connections between the input and the output, the new architecture of the neural network can have both global features and regional features extracted from the input. The global connections put more emphasis on the whole picture and determine the global trend of the predicted curve, while the regional connections concentrate on each point and modify the prediction locally. Back-propagation algorithm is used in the modeling. A basic structure of neural network designed for this problem is discussed. Then to overcome its drawbacks, we propose a new structure.
DOI：
10.1109/86.895950
发表时间：
2000-12-01
期刊：
IEEE TRANSACTIONS ON REHABILITATION ENGINEERING
影响因子：
--
作者：
Au, ATC;Kirsch, RF
通讯作者：
Kirsch, RF