Abstract

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. The subjects executed a 30-min computer task to simulate real work conditions while working at an ergonomically designed workstation. Six-channel intramuscular EMG signals were recorded from two positions of the upper trapezius muscle. The EMG signals were decomposed into individual motor unit action potential trains using EMG-LODEC. The study design enabled us first to study the dependence of intramuscular analysis on the insertion points and second to test the accuracy of the decomposition technique under laboratory conditions during a real experiment. The two positions yielded 887 motor units--452 located in position 1 and 435 in position 2. Although the numbers of detected action potentials were strongly correlated between the two insertion positions, different motor units were mostly recorded. In particular, the detection of continuously active motor units is specific for the selected insertion points and may not be representative of a muscle, not even for parts with common functions. The approach for the quantitative evaluation of the decomposition technique was to independently decompose two signals that were simultaneously detected by separate sets of wire electrodes placed close to each other in the muscle. Common trains discovered in each signal were compared for consistency. A cross-correlation analysis was performed to find corresponding motor unit pairs that were concurrently active. Concurrently active motor units were found in six subjects. For these motor units the extent of simultaneous occurrence of motor unit action potentials between the two positions ranged from 23% to 78% depending on the distinction of the single motor units and the number of superimposed motor unit action potentials. High concordance was seen in 3 out of the 15 motor unit pairs. Based on the results, EMG-LODEC is capable of providing reliable decompositions with satisfying accuracy and reasonable processing time. EMG-LODEC is suitable for the study of motor unit discharge patterns and recruitment order in subjects with and without musculoskeletal pain during long-term measurements to study work-related musculoskeletal disorders.

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