The paper discusses how recognition of individual and combined muscular activation modes (functions) and the prediction of intended such modes can be accomplished by identifying parameters of noninvasive surface EMG signals. It outlines the mathematical analysis of surface EMG signal to facilitate such recognition and related prediction, including recognition of intention (in terms of attempts)...

background: surface electromyography (semg) of muscles is a non-invasive tool that can be helpful in the assessment of muscle function and some motor control evaluations. a loss of force, known as muscle fatigue is accompanied by changes in muscle electrical activity. one of the most commonly used surface emg parameters which reflects paraspinal muscle fatigue during different tasks and positio...

The surface electromyographic (EMG) signal is often contaminated by some degree of baseline noise. It is customary for scientists to subtract baseline noise from the measured EMG signal prior to further analyses based on the assumption that baseline noise adds linearly to the observed EMG signal. The stochastic nature of both the baseline and EMG signal, however, may invalidate this assumption....

Farina, Dario, Roberto Merletti, and Roger M. Enoka. The extraction of neural strategies from the surface EMG. J Appl Physiol 96: 1486–1495, 2004; 10.1152/japplphysiol.01070.2003.—This brief review examines some of the methods used to infer central control strategies from surface electromyogram (EMG) recordings. Among the many uses of the surface EMG in studying the neural control of movement, ...

EMG signals are electromyogram signals generated by firing of MUs (motor units) in muscle fibers. The decomposition of EMG signal of a muscle provides useful information for the diagnosis of neuro-muscular diseases by physician and neurologist. In decomposition of EMG signal different MUAPs (Motor Unit Action Potentials) are classified into different categories. This paper gives a review of dif...