This study developed a new muscle fatigue feature based on sEMG signals. The evolved
feature is combining 11 traditional muscle fatigue sEMG parameters to optimally classify the …

Surface Electromyography (sEMG) activity of the biceps muscle was recorded from nine
subjects. Data were recorded while subjects performed dynamic contraction until fatigue …

Genetic programming is used to generate a solution that can classify localized muscle
fatigue from filtered and rectified surface electromyography (sEMG). The GP has two …

Surface Electromyography (sEMG) activity of the biceps muscle was recorded from ten
subjects. Data were recorded while subjects performed isometric contraction until fatigue …

Surface Electromyography (sEMG) activity of the biceps muscle was recorded from ten
subjects performing isometric contraction until fatigue. The signals were segmented into two …

Muscle fatigue is the decrease in its ability to generate a target force. In this paper, a novel
muscle fatigue detection algorithm based on sEMG signal is developed. Short-time Fourier …

The purpose of this study was to develop an algorithm for automated muscle fatigue
detection in sports related scenarios. Surface electromyography (sEMG) of the biceps …

Surface electromyogram (sEMG) signal is commonly used for muscle fatigue analysis in
clinical rehabilitation studies. Prediction results based on sEMG signals are promising …

In this work, an attempt has been made to differentiate surface electromyography (sEMG)
signals under muscle fatigue and non-fatigue conditions with multiple time window (MTW) …

In this research an algorithm was developed to classify muscle fatigue content from dynamic
contractions, by using a genetic algorithm (GA) and a pseudo-wavelet function. Fatiguing …