Introduction It is electromyogram (EMG) that represents interference signals of electrical activities in many motor units (MUs). An EMG decomposition method is the procedure by which the signal is classified into its constituent motor unit action potential trains (MUAPTs). So far the classification to each MUAPT in multi-channel EMGs by means of an EMG decomposition method is directly performed...

Wavelet-based signal processing has become commonplace in the signal processing community over the past decade.Wavelet analysis is often very effective because it provides a simple approach for dealing with local aspects of a signal. Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. ...

Traditionally, in clinical electromyography (EMG), neurophysiologists assess the state of the muscle by studying basic units of an EMG signal, which are referred to as motor unit action potentials (MUAPs). Information regarding themorphology and rate of occurrence ofMUAPs is often used for diagnosis of neuromuscular disorders. In addition, recent studies have shown that the analysis of the ener...

This report describes an early version of a technique for decomposing surface electromyographic (sEMG) signals into the constituent motor unit (MU) action potential trains. A surface sensor array is used to collect four channels of differentially amplified EMG signals. The decomposition is achieved by a set of algorithms that uses a specially developed knowledge-based Artificial Intelligence fr...

Background Electromyographic (EMG) signal decomposition is the process by which an EMG signal is decomposed into its constituent motor unit potential trains (MUPTs). A major step in EMG decomposition is feature extraction in which each detected motor unit potential (MUP) is represented by a feature vector. As with any other pattern recognition system, feature extraction has a significant impact...

We propose and test a tool to evaluate and compare EMG signal decomposition algorithms. A model for the generation of synthetic intra-muscular EMG signals, previously described, has been used to obtain reference decomposition results. In order to evaluate the performance of decomposition algorithms it is necessary to define indexes which give a compact but complete indication about the quality ...

{ The paper presents three deterministic and one statistical procedure for a possible decomposition of superimposed signals modelled as multichannel, linear, time-invariant system outputs. A brief theoretical background is given for short-time cepstral analysis, wavelet transform, iterative parametric search, and higher-order statistics approach. The methods are evaluated according to the resul...