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 (sEMG) has been widely applied to disease diagnosis, pathologic analysis and rehabilitation evaluation. It is the nonlinear summation of the electrical activity of the motor units in a muscle and can reflect the state of neuromuscular function. Traditional linear and statistical analysis methods have some significant limitations due to the short-term stationary and lowe...

AIM The aim of this study is to prove that facial surface electromyography (sEMG) conveys sufficient information to predict 3D lip shapes. High sEMG predictive accuracy implies we could train a neural control model for activation of biomechanical models by simultaneously recording sEMG signals and their associated motions. MATERIALS AND METHODS With a stereo camera set-up, we recorded 3D lip ...

It is clear that the surface electromyographic-based (sEMG) human-machine interface (HMI) shows a reduction in stability when the muscle fatigue occurs. This paper presents an improved incremental training algorithm that is based on online support vector machine (SVM). The continuous wavelet transform is used to study the changes of sEMG when muscle fatigue occurs, and then the improved online ...

Effect of contraction intensity [100%, 75%, 50%, and 25% maximum voluntary contraction (MVC)] and movement velocity [0 degrees (isometric)], 50 degrees, 100 degrees, 200 degrees, and 400 degrees/sec. [isovelocities]) on root mean square amplitude (SEMG-RMS) and median frequency power spectrum (SEMG-MNF) of vastus lateralis (VL) surface electromyography was investigated with ten healthy female u...

OBJECTIVE Patients suspected of having swallowing disorders, could highly benefit from simple diagnostic screening before being referred to specialist evaluations. The article analyzes various instrumental methods of dysphagia assessment, introduces surface electromyography (sEMG) to carry out rapid assessment of such patients, and debates proposed suggestions for sEMG screening protocol in ord...

Gesture recognition in non-intrusive muscle-computer interfaces is usually based on windowed descriptive and discriminatory surface electromyography (sEMG) features because the recorded amplitude of a myoelectric signal may rapidly fluctuate between voltages above and below zero. Here, we present that the patterns inside the instantaneous values of high-density sEMG enables gesture recognition ...

In this paper, a real-time experimental of Hand Gesture sEMG signal for Wearable wrist watch is proposed. The raw SEMG signals been captured from SEMG amplifier, up to 8 channels of NI-DAQ card responses data will be combined and a fine tuning step by using pattern classification. The database then been build and use for real-time experimental control classification. Captured data will send thr...

BACKGROUND Genioglossus myoelectric activity is of great significance in evaluating clinical respiratory function. However, there is a tradeoff in genioglossus EMG measurement with respect to accuracy versus convenience. OBJECTIVE This paper presents a way to separate the characteristics of genioglossus myoelectric activity from multi-channel mandible sEMG through independent component analys...

Conventionally, gesture recognition based on nonintrusive muscle-computer interfaces required a strongly-supervised learning algorithm and a large amount of labeled training signals of surface electromyography (sEMG). In this work, we show that temporal relationship of sEMG signals and data glove provides implicit supervisory signal for learning the gesture recognition model. To demonstrate thi...