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 impac...

Background: Electromyographic (EMG) signals obtained from a contracted muscle contain valuable information on its activity and health status. Much of this information lies in motor unit potentials (MUPs) of its motor units (MUs), collected during the muscle contraction. Hence, accurate estimation of a MUP template for each MU is crucial. Objective: To investigate the possibility of improv...

Since past few years, researchers have been concentrating on the classification of Electromyography Signal. This method is very useful in diagnosing the neuro-muscular disorders, which consists of wide spread diseases affecting peripheral nervous system. Progressive muscle weakness is the major form of these disorders. Out of various proposed methods, scholars are commonly focusing on Neural Ne...

motor units (mus) reflect the function of the central nervous motor system. thus, the estimated mu number is a good option to investigate the functional movement disorder in the parkinson’s disease (pd). the purpose of this study was to compare the estimated mus number in the medial gastrocnemius (mg) muscle of the normal rats and those with the parkinsonism. the mg muscle of two age-matched gr...

A new feature extraction / classification method for High Density surface ElectroMyoGraphy (HD sEMG) Motor Unit Action Potential (MUAP) decomposition using 2D shape and energy distribution features is presented and experimentally tested.