HAND GESTURE CLASSIFICATION BASED ON EMG SIGNALS

Abstract

This paper presents EMG signals processing and classification of hand gesture. Used classifiers are based on k nearest neighbors method, support vector machine method and linear discriminant analysis.The classifier based on k nearest neighbors has the best performance. Results shows need for a better form of signal normalization, in order to improve classification. Also, it would be a good to train a neural network and test its performance.