Prospective Synthesis for Evaluation System of EMG Information Signal-An Overview

Abstract

Human nerve signal are being extensively studied in recent times due to their undeniable control on human physiological system. These Myoelectric signals have been and continue to be analyzed for medical data processing devices and human assistance robots. In this paper, a prospective procedure to analyze EMG signals has been proposed which synthesizes the techniques that have been evaluated individually to perform designed processing. Initially the paper briefly reviews the conventional EMG acquisition method followed by the overview of the proposed data analysis techniques that involve the segmenting data, disregarding redundant data and classification of significant data. The paper briefly reviews KF-LDA design that assembles KF's ability to estimate non-linear progressions and stable steady state LDA classification. The proposed evaluation system synthesizes the use of ANN and KF-LDA for data classification. Furthermore, the broad areas of application for EMG evaluation are listed followed by a summarized conclusion.