A successful pre-processing stage based on wavelet denoising algorithm for electromyography (EMG) signal recognition is proposed. From the limitation of traditional universal wavelet denoising, the optimal weighted parameter is assigned for universal thresholding method. The optimal weight for increasing EMG recognition accuracy is 50–60% of traditional universal threshold with hard transformat...

Problem statement: The social demands for the Quality Of Life (QOL) are increasing with the exponentially expanding silver generation. To improve the QOL of the disabled and elderly people, robotic researchers and biomedical engineers have been trying to combine their techniques into the rehabilitation systems. Various biomedical signals (biosignals) acquired from a specialized tissue, organ, o...

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...

An algorithm is proposed for processing and analyzing surface electromyography (SEMG) signals using wavelet transform and Higher Order Statistics (HOS). EMG signal acquires noise while travelling though different media. Wavelet denoising is performed in this research for initial EMG signal processing. With the appropriate choice of the Wavelet Function (WF), it is possible to remove interferenc...

Muscle synergies calculated from electromyography (EMG) data identify weighted groups of muscles activated together during functional tasks. Research has shown that fewer synergies are required to describe EMG data of individuals with neurologic impairments. When considering potential clinical applications of synergies, understanding how EMG data processing impacts results and clinical interpre...

There are several methods available for EMG(Electromyography) based user intent detection, wherein muscle activation has been recognized by different approaches.Even thoughEMG detection and processing has been done by many other researchers, need of improved model is still rising. The notion of this study is to propound a novel approach whereby quantification of EMG signal for foot flexion can ...

This work deals with electromyography (EMG) signal processing for the diagnosis and therapy of different muscles. Because correct muscle activity measurement strongly noised EMG signals is major hurdle in medical applications, a raw measured should be cleaned factors like power network interference ECG heartbeat. Unfortunately, there are no completed studies showing full multistage recordings. ...

This paper presents a developed tool capable of decomposing electromyographic signals (EMG) named EMG Decomposition. The main aim of this software is to extract and to visualize motor unit action potentials (MUAPs) extracted from EMG signals during a muscular contraction. The identification and clustering of MUAPs that show similar features is most important for the definition of such cluster s...

The technology of EMG recording is relatively new. There are still limitations in detection and characterization of existing nonlinearities in the surface electromyography (SEMG). Wavelet packets are advance and effective method for analysing signal processing work. EMG signal represents the neuromuscular activities and analysis of EMG signals can lead to diagnose myopathy and neuropathy relate...