This study aims at proposing an efficient method for automated electrocardiography (ECG) artifact removal from surface electromyography (EMG) signals recorded from upper trunk muscles. Wavelet transform is applied to the simulated data set of corrupted surface EMG signals to create multidimensional signal. Afterward, independent component analysis (ICA) is used to separate ECG artifact componen...

Electrocardiogram recordings (ECG) are obtained from the heart. Some sections of the recorded ECG may be corrupted by electromyography (EMG) noise from the muscle. In real situations, exercise test ECG recordings and long term recordings, are often corrupted by muscle artifacts. These EMG noise needs to be filtered before data processing. In this paper, wavelet transform is applied to remove th...

Electromyography signal can be used for biomedical applications. It is complicated in interpretation, so it acquires advanced methods for detection, decomposition, processing, and classification. The techniques of EMG signal analysis such as: filtering, wavelet transform, and modeling will be presented in this paper to provide efficient and effective ways of understanding the signal. A comparis...

The EMG signal indicates the electrophysiological response to daily living of activities, particularly to lower-limb knee exercises. Literature reports have shown numerous benefits of the Wavelet analysis in EMG feature extraction for pattern recognition. However, its application to typical knee exercises when using only a single EMG channel is limited. In this study, three types of knee exerci...

This paper considers the decomposition of surface electromyograms (SEMG) using higher-order statistics (HOS). Modelling surface EMG by a MIMO system whose inputs in the form of innervation pulse trains are considered independent identically distributed (i.i.d.) random white noise, the system identification methods based on higher-order statistics may be introduced. We disclose how a two-phase p...

Electromyographic signals contaminated with noise during the acquisition process affect results of follow-up applications such as disease diagnosis, motion recognition, gesture and human–computer interaction. This paper proposes a denoising technique based on variational mode decomposition (VMD) for both surface electromyography (sEMG) intramuscular (iEMG). sEMG iEMG obtained from 5 healthy sub...

Biceps brachii muscle illness is one of the common physical disabilities that requires rehabilitation exercises in order to build up the strength of the muscle after surgery. It is also important to monitor the condition of the muscle during the rehabilitation exercise through electromyography (EMG) signals. The purpose of this study was to analyse and investigate the selection of the best moth...