Single motor unit and spectral surface EMG analysis during low-force, sustained contractions of the upper trapezius muscle.

Intramuscular and surface electromyographic (EMG) activities were recorded from the left and right upper trapezius muscle of eight healthy male subjects during 5-min long static contractions at 2% and 5% of the maximal voluntary contraction (MVC) force. Intramuscular signals were detected by wire electrodes while surface EMG signals were recorded with linear adhesive electrode arrays. The surface EMG signals were averaged using the potentials extracted from the intramuscular EMG decomposition as triggers.

Trapezius muscle motor unit activity in symptomatic participants during finger tapping using properly and improperly adjusted desks.

Work-related musculoskeletal disorders in the neck-shoulder area and upper extremities are common among computer users, especially women. We compared temporal changes of motor unit (MU) activation in the trapezius muscle during finger tapping using both appropriate and inappropriate ergonomic desk adjustments. Sixteen intensive and nonintensive computer users with either moderate or severe musculoskeletal disorders participated in the study.

Motor unit identification in two neighboring recording positions of the human trapezius muscle during prolonged computer work.

Work-related shoulder-neck pain is a major health risk in computer operators. To understand the physiological mechanisms behind the development of these disorders, EMG recordings of some minutes up to several hours must be accurately decomposed. For this reason we developed EMG-LODEC, an automatic decomposition software program, especially designed for multi-channel long-term recordings of signals detected during slight muscle movements.

A software package for the decomposition of long-term multichannel EMG signals using wavelet coefficients.

This paper presents a method to decompose multichannel long-term intramuscular electromyogram (EMG) signals. In contrast to existing decomposition methods which only support short registration periods or single-channel recordings of signals of constant muscle effort, the decomposition software EMG-LODEC (ElectroMyoGram LOng-term DEComposition) is especially designed for multichannel long-term recordings of signals of slight muscle movements. A wavelet-based, hierarchical cluster analysis algorithm estimates the number of classes [motor units (MUs)], distinguishes single MUAPs from superpositions, and sets up the shape of the template for each class.