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

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.

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

“…The algorithm was specifically designed for longterm applications and the reliability of its results has been shown in previous studies (Zennaro et al 2002(Zennaro et al , 2003b. The program uses wavelet coefficients, template matching, template updating, and superposition resolution to identify the individual firing times of the MUs.…”

Inter-operator agreement in decomposition of motor unit firings from high-density surface EMG

“…Two electrodes within the same muscle have a chance to record from the same MUs. By simultaneous data acquisition, independent analysis and cross-correlation of the results, the limit of accuracy can be determined (Mambrito and De Luca, 1984;McGill et al, 2004;Zennaro et al, 2003). This approach is not easily translated to surface EMG.…”

Non-invasive characterization of single motor unit electromyographic and mechanomyographic activities in the biceps brachii muscle

“…The analysis of motor unit (MU) properties in voluntary contractions allows the investigation of the strategies adopted by the central nervous system to control the muscle and their adaptation to conditions such as ageing, fatigue, exercise, pathology, or pain [1,10,12,21,24]. Multi-channel surface electromyographic (EMG) action potentials provide information on single MU membrane characteristics, such as conduction velocity [6,7].…”