Electromyogram (EMG) Signal Categorization in Parkinson’s Disease Tremor Detection by Applying MLP (Multilayer Perceptron) Technique: A Review

Abstract

In recent years, there has been extensive interest in the revelation of different technologies for artificial neural network (ANN) application in various classification of biomedical signals. Several publications have focused on diverse applications of ANN techniques for biomedical signals classification, detection, and processing. This review work gives an overview on the multilayer perceptron (MLP) technique of ANN and how this technology is useful for the classification of EMG signal. This paper will be interesting for those researchers who are studying the classification EMG signal for tremor detection in Parkinson’s disease. Many researchers have worked and also working on Parkinson’s disease tremor by using EMG signal and classifying its feature using ANN. Among those various techniques, MLP technique is highlighted in this work for the classification of EMG signal. The core center of this paper is to review the evolution and research works related to the topic mentioned above.