1. Abstract: Appropriate cancellation of the baseline fluctuation (BLF) is an important issue when recording EMG signals as it may degrade signal quality and distort qualitative and quantitative analysis. We present statistical and filter-design approach for cancellation of the BLF based on several signal processing techniques used sequentially. The methodology is to estimate the spectral conte...

Electromyography (EMG) is a bio signal that is formed by physiological variations in the state of muscle fibre membranes. Pattern recognition is one of the fields in the bio-signal processing which classified the signal into certain desired categories with subject to their area of application. This study described the classification of the EMG signal based on human body percentile using Self Or...

In order to control the movement of a cybernetic actuator the EMG signal is generally used as a source of command This signal has to be processed in order to extract relevant features, which are then classified. Many schemes exist today in both feature extr action and classification, each one claiming to reduce the error rate and there has been some approaches in order to assess the input-outpu...

In the present paper we have described a system for acquiring, processing and decomposing EMG signals for the purpose of extracting as many motor unit action potential trains as possible with the greatest level of accuracy. This system consists of 4 main sections. The first section consists of methodologies for signal acquisition and quality verification. Three channels of EMG signals are acqui...

Goal  This work aims at designing and implementing FPGA based module to process and perform pattern recognition on EMG (Electromyography) signals that are received from human muscular movements that are otherwise complex to analyze on some standard methods. Purpose  On the completion of this work we want to gain proficiency in following areas  Studying the available algorithms for processing...

The purpose of this research is to select the best features to have a high rate of motion classification for controlling an artificial hand. Here, 19 EMG signal features have been taken into account. Some of the features suggested in this study include combining wavelet transform with other signal processing techniques. An assessment is performed with respect to three points of view: (i) classi...

Electromyography (EMG) is the study of electrical activity of muscle and it form valuable information in the diagnosis of neuromuscular disorders. EMG signal may be degraded by a noise; it is in the baseline of EMG signal. It is called baseline fluctuation of EMG signal. Baseline fluctuation distorts qualitative and quantitative analysis. The present work focus on various techniques and their c...