Electromyography gives an electrical representation of neuromuscular activation associated with a contracting muscle. The electromyography signal acquires noise while travelling though different media. The wavelet transform is employed for removing noise from surface electromyography (SEMG) and higher order statistics are applied for analysing the signal. With the appropriate choice of wavelet,...

Recent works have demonstrated that the Independent Components (ICs) of simultaneously-recorded surface Electromyography (sEMG) recordings are more reliable in monitoring repetitive movements and better correspond with ongoing brain-wave activity than raw sEMG recordings. In this paper we propose to detect single muscle activation, when the arms reach a target, by means of ICs time-scale decomp...

This study looks at various parameters, derived from surface electromyography (sEMG) and Near Infrared Spectroscopy (NIRS) and their relationship in muscle fatigue during a static elbow flexion until exhaustion as well as during a semidynamic exercise.We found a linear increasing trend for a corrected amplitude parameter and a linear decreasing slope for the frequency content of the sEMG signal...

This paper explores the application of multifractal detrended fluctuation analysis (MF-DFA) on the nonlinear characteristics of correlation between operation force and surface electromyography (sEMG), which is an applied frontier of human neuromuscular system activity. We established cross-correlation functions between the signal of force and four typical sEMG time-frequency domain index sequen...

Surface electromyography is the technique for measuring levels of muscle activity. When a muscle contracts, electrical activity generated as action potentials propagate along the muscle fibers. There are two types of Surface EMG (SEMG)-Static scanning SEMG and Dynamic SEMG. In Dynamic SEMG, electrodes are attached to the skin and muscle activity is measured and graphed as the patient moves thro...

Our recent efforts towards developing a practical surface electromyography (sEMG) based silent speech recognition interface have resulted in significant advances in the hardware, software and algorithmic components of the system. In this paper, we report our algorithmic progress, specifically: sEMG feature extraction parameter optimization, advances in sEMG acoustic modeling, and sEMG sensor se...

A new feature extraction / classification method for High Density surface ElectroMyoGraphy (HD sEMG) Motor Unit Action Potential (MUAP) decomposition using 2D shape and energy distribution features is presented and experimentally tested.

In this paper, an adaptive human-machine interaction (HMI) method that is based on surface electromyography (sEMG) signals is proposed for the hands-free control of an intelligent wheelchair. sEMG signals generated by the facial movements are obtained by a convenient dry electrodes sensing device. After the signals features are extracted from the autoregressive model, control data samples are u...

Biofeedback is a process in which biological information is measured and fed back to a patient and clinician for the purpose of gaining increased awareness and control over physiological domains. Surface electromyography (SEMG), a measure of muscle activity, allows both a patient and clinician to have direct and immediate access to muscle functioning that is not possible with manual palpation o...

High-density surface electromyography (HD-sEMG) is to record muscles' electrical activity from a restricted area of the skin by using two dimensional arrays of closely spaced electrodes. This technique allows the analysis and modelling of sEMG signals in both the temporal and spatial domains, leading to new possibilities for studying next-generation muscle-computer interfaces (MCIs). sEMG-based...