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This paper presents a classification method for multi-class classification of electromyography (EMG) signals from eight hand movements. The data were collected from 15 subjects. The EMG signals were extracted using 16 time-domain feature extraction methods. The 16 features are reduced using principal component analysis (PCA) to enhance the classification accuracy. The features results from PCA are...
This work gives a comparative study on the use of Linear Discriminant Analysis (LDA), Artificial Neural Network (ANN) and Naive-Bayes Classifier (NBC) for recognizing various locomotion modes using parameters derived from the transient EMG signals taken from healthy subjects and thus provide a better control mechanism for lower limb prosthesis. These classifiers have been taken into consideration...
We develop a multi-channel electromyogram acquisition system base on the programmable system on chip (PSOC) microcontroller to control robotic arm. The array of 4x4 surface electrodes which invents from the low-cost EKG electrodes is used as the input sensor. B-spline interpolation technique has been utilized to map the EMG signal on the muscle surface. The topological mapping of the EMG is then analyzed...
Recent approaches in multifunction myoelectrically controlled prosthetic devices revealed that dimensionality reduction plays a significant role in the overall system performance. In this paper, a new feature selection method is developed based on a mixture of particle swarm optimization (PSO) method and the concept of mutual information (MI). The new method, termed PSO-MI, is adopted as a dimensionality...
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