Sensitivity of trapezius electromyography to differences between work tasks — influence of gap definition and normalisation methods
Introduction
Surface electromyography (EMG) has a long tradition, and broad applications, for measuring muscular activity [6], [13], [14], [15]. In studies of occupational musculoskeletal disorders, EMG has been used to obtain quantitative measures of physical exposure. EMG reflects the internal load and is thus dependent on both the external load, implied by the task, and individual factors. Due to the high prevalence and localisation of neck and shoulder disorders, many studies have focused on the trapezius muscle. The trapezius muscle is superficial, and thus accessible for EMG. However, to obtain — and validate — high-quality EMG recordings, during whole-day measurements in field studies, methodological factors should be considered [10].
To compensate for the large (order of a magnitude) inter-individual variation in the derived EMG amplitude, normalisation to a reference contraction is usually performed [19]. This contraction — usually isometric — may be either maximal or submaximal and performed in a variety of postures, and, for the submaximal contraction, at various load levels. However, the effect of various methods of normalisation, on inter-individual and inter-task variability is not well known [4].
The characterisation of muscular activity in quantitative terms may be performed in a practically unlimited number of ways, e.g., [16], [17], [18], [21], [22], [26]. The 10th, 50th and 90th percentiles of the amplitude distribution (APDF=amplitude probability distribution function) [16] are frequently used. However, these measures may not be the optimal ones for predicting risk of muscular disorders in repetitive work; work that is characterised by sustained, low level muscle activity [11], [32]. Consequently, information in the muscle activity at low load levels, e.g., the occurrence of (short) periods of EMG silence, “gaps” [26], has attained an increasing interest. Gap frequency can predict the development of neck/shoulder disorders [28]. Moreover, subjects with neck/shoulder disorders displayed lower relative duration of muscular rest during work, as compared to subjects without disorders [9]. Both these findings are consistent with the “Cinderella hypothesis” [8]. However, the knowledge of the effects of normalisation methods, the selected threshold level and gap duration criterion, all of which are likely to have a strong influence on the summary measure of the EMG, is limited.
The aim of this study was to determine the sensitivity of trapezius EMG gap frequency, relative duration of muscular rest and various percentiles of the amplitude distribution, to differences between occupational tasks and between individuals. In investigating this aim, emphasis was placed on evaluating the role of changes in the criteria for defining gaps and muscular rest, and of normalisation methods.
Section snippets
Materials and methods
Data are from a cross-sectional study of hospital cleaners and office workers [22]. On a typical workday the subject's tasks were continuously noted and bilateral trapezius EMG was recorded for the full day. The fundamental tasks (e.g., cleaning, office work and pauses) were synchronised with the EMG data.
Noise level and reference contractions
For the right trapezius muscle the mean noise level was 0.95 (SD 0.27, range 0.41–1.55) μV, mean MVE activity 863 (SD 356, range 123–1988) μV, and the mean RVE value 17.9% (SD 6.7%, range 7.1–38.3%) of MVE. The mean noise to MVE ratio was 0.13% (SD 0.095%, range 0.04–0.69%), and the mean noise to RVE ratio was 0.78% (SD 0.45%, range 0.27–3.0%). The corresponding values were similar for the left side: 1.03 μV, 860 μV, 18.0% MVE, 0.13% and 0.83%, respectively.
Numeric values of gap frequency, muscular rest and percentiles of the amplitude distribution
The numeric value of the gap frequency
Discussion
This study demonstrates that the post-processing method used to analyse the trapezius EMG signal had an important effect on the derived summary measures. A short gap duration criterion and normalisation to RVE, rather than MVE, produced EMG measures with advantageous characteristics. For gap frequency, the selection of threshold level had a decisive effect on sensitivity to differences in tasks, as well as between individuals.
The present tasks represent common ones in modern working life.
Acknowledgements
This study was supported by the Medical Research Council, the Swedish Council for Work Life Research (including Change@Work), the Swedish National Institute for Working Life (Co-operative for Optimization of industrial production systems regarding Productivity and Ergonomics; COPE), the Medical Faculty of Lund University, and the Swedish Council for Planning and Co-ordination of Research. Ms Lothy Granqvist and Jeannette Unge Byström gave skilful technical assistance.
Gert-Åke Hansson received his MSc in Electrical Engineering from Lund Institute of Technology, Sweden in 1976. He has developed and applied methods for biomedical measurements on both animals and humans. His present research interest is the development of methods for measuring and analysing physical work load with relevance to epidemiological studies of musculoskeletal disorders of the neck and upper limbs. This has resulted in the development of an inclinometer, based on three-axial
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Gert-Åke Hansson received his MSc in Electrical Engineering from Lund Institute of Technology, Sweden in 1976. He has developed and applied methods for biomedical measurements on both animals and humans. His present research interest is the development of methods for measuring and analysing physical work load with relevance to epidemiological studies of musculoskeletal disorders of the neck and upper limbs. This has resulted in the development of an inclinometer, based on three-axial accelerometers, and ambulatory data loggers for whole day recordings of EMG and joint postures and movements. In addition, he has developed and applied methods for assessing muscular fatigue from EMG recordings.
Catarina Nordander received her MD from Lund University, Sweden in 1989. Since then she has been a physician at the Department of Occupational and Environmental Medicine at Lund University Hospital. Her main research interests are ergonomics and the application of surface electromyography, measured in working situations, on the risk of developing musculoskeletal disorders.
Paul Asterland was educated in Electrical Engineering at Lund Institute of Technology, Sweden. He has developed both hardware and software for data acquisition. At present he is developing software for the analysis of whole day measurements of EMG, as well as joint postures and movements.
Kerstina Ohlsson received her Dr Med Sc in 1995 from the Department of Occupational and Environmental Medicine at Lund University Hospital, Sweden. Her thesis focused on musculoskeletal disorders of the neck and upper limbs among women with industrial repetitive work. She is now engaged in research on the relation between physical work load and the development of musculoskeletal disorders.
Ulf Strömberg received his MSc and PhD degrees in mathematical statistics from Lund University, Sweden. He is Associate Professor of Medical Statistics at the Institute of Laboratory Medicine, Department of Occupational and Environmental Medicine, Lund University, Sweden. He has authored and co-authored more than 35 refereed journal papers in the fields of biostatistics and epidemiology. His major research interests focus on applied biostatistics and epidemiologic methods.
Staffan Skerfving received his MD from the Karolinska Institute in Solna, Sweden, in 1966 and his PhD in 1972. He is currently Professor of Occupational Medicine at Lund University. His research is focused on, i.a., the relationship between occupational mechanical exposure and musculoskeletal disorders.
David Rempel received his MD from the University of California at San Francisco in 1982 and his MPH from the University of California at Berkeley in 1981. He is currently Associate Professor of Medicine at the University of California at San Francisco and Associate Professor of Bioengineering at UC Berkeley. He is also Director of the Ergonomics Graduate Training Program at the University of California, Berkeley. His research is focused on understanding mechanisms of upper extremity tendon, nerve, and muscle injury and repair associated with repeated and forceful loading of the hands at work. Dr Rempel has conducted epidemiologic and laboratory studies to determine the effects of hand tool design and tasks on hand and arm fatigue, pain, impairment, and muscle load.