Prediction Model of Horse Elbow Joint Flexion Motion Based on BP Neural Network
The high precision of the flexion of the elbow joint is very important in the development of devices based on myoelectric control. In this paper, a new method based on BP neural network for predicting the flexion of the elbow joint is proposed. The method uses time domain features to collect BP signals from the biceps using Ag (AgCl) electrodes. To test the proposed method, the method was tested using Root Mean Square Error (RMSE) and Pearson Correlation Coefficient (CC). In this study, the RMSE and CC values were 6.9° to 17.5° and 0.93 to 0.99, respectively. The experimental results demonstrate the effectiveness of the proposed method based on BP neural network for the prediction of flexion of the elbow joint.