Methods for measuring physical workload with relevance for musculoskeletal disorders of neck and upper limb

Abstract: Work-related musculoskeletal disorders of the neck and upper limb are a major problem. Women in repetitive manual work is one large affected group. Preventive actions are hampered by the lack of knowledge regarding quantitative exposure-response relations for physical workload. The present work shows, that available electrogoniometers are, with a sampling frequency of 20 Hz, feasible for measuring wrist positions and calculation of movements. The main error, caused by crosstalk, does not invalidate the results. Mean power frequency is a suitable generalized measure of repetitiveness. Inclinometers, based on 3 one-axial accelerometers, were developed. These provide, in combination with comprehensive data processing, measures of the forces that act on the body. During ordinary occupational work, data can be interpreted as inclination, e.g., of the head, upper back and arms. A questionnaire, regarding physical workload, was validated. It had a low agreement with direct measurements and showed differential misclassification due to musculoskeletal complaints and gender. Hence, direct measurements are preferable in epidemiological studies. We found a quantitative exposure-response relation between repetitive wrist movements and wrist/hand disorders among women in repetitive manual work. No relation between muscular load, using task-related electromyography (EMG) measures of "static" load, and neck/shoulder disorders were observed. To characterize low muscular load in the trapezius muscle, muscular rest in EMG is suitable for describing work tasks, while gap frequency rather reflects individual properties. Normalization to a submaximal reference contraction, rather than a maximal one, is preferable for characterization of muscular load in different work tasks. The developed methods can, combined with high-capacity data loggers, give whole-day ambulatory recordings of physical workload, and have a potential in evidence-based risk assessment and prevention.