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. Using three channels and a weighted averaging method to track action potential (AP) shape changes improve the analysis. In the last step, nonclassified segments, i.e., segments containing superimposed APs, are decomposed into their units using class-mean signals. Based on experiments on simulated and long-term recorded EMG signals, our software is capable of providing reliable decompositions with satisfying accuracy. EMG-LODEC is suitable for the study of MU discharge patterns and recruitment order in healthy subjects and patients during long-term measurements.

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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. The conduction velocity of single motor units (MUs) was estimated over time from the averaged surface potentials while average rectified value and mean power spectral frequency were computed over time from 0.5 s epochs of surface EMG signal. It was found that (1) MUs were progressively recruited after the beginning of sustained contractions of the upper trapezius muscle at 2% and 5% MVC, (2) the conduction velocity of the MUs active since the beginning of the contraction significantly decreased over time, and (3) although the CV of single MUs significantly decreased, the mean power spectral frequency of the surface EMG did not show a consistent trend over time. It was concluded that spectral surface EMG analysis, being affected by many physiological mechanisms, may show limitations for the objective assessment of localized muscle fatigue during low force, sustained contractions. On the contrary, single motor unit conduction velocity may provide an early indication of changes in muscle fiber membrane properties with sustained activity.

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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. Six-channel intramuscular electromyographic (EMG) signals and 2-channel surface EMG were recorded from 2 positions of the trapezius muscle. A statistically significant increase in activity was observed with a desk adjusted 5 cm higher than appropriate and was attributable mainly to increased duration of MU activity. Participants with severe symptoms activated more MUs, and these were also active longer. In women, on average, MUs were active nearly twice as long as in men during the same tapping task. This study demonstrates that it is possible to evaluate ergonomic topics on the MU level and that incorrectly adjusted office equipment, in addition to motor demands imposed by the work task, results in prolonged activity of MUs. A potential application of this research is an increased awareness that certain individuals who work with incorrectly adjusted office equipment may be at greater risk of developing work-related musculoskeletal disorders.