A study stressing the need for a static postural force model for work analysis

Abstract

The maximum endurance time (MET) in static force exertions was used as a parameter for the assessment of five working postures. By applying the methodology of Rohmert to the construction of a general model for static muscular work and evaluating the measured MET results, the need for a new static posture model has been shown. The aim of the present pilot study was to test MET in load situations that would indicate when the general model can be used or when a new static postural force model is needed. Subjects exerted static postural forces at different load levels until exhaustion. In the first two postures, the strain was concentrated on the upper limbs, where active forces (muscular) play a key-role and justify the use of the model. In the remaining postures, the strain affected mainly the back/trunk, where the mechanical equilibrium of the body is brought about by active (muscles) and passive (skeleton and ligaments) structures. During the tests electromyographic (EMG) measurements of selected muscles (objective measurements) as well as rated perceived exertion (RPE; subjective measurements on Borg's CR-10 scale) were recorded. The results show that the maximum endurance times in upper extremity postures are predicted by the general model whilst in the back/trunk postures the measured MET was longer than predicted by the model. New models are presented for static postural force on the back. The EMG measurements supported the conclusion that the muscles studied play a key role in the chosen upper-extremity postures but gave no clear indication in the back-oriented postures. Ratings of perceived exertion coincided with the EMG measurements in upper extremity postures and proved to be a good substitute for measurement and calculation of the load levels studied. The initial RPE can therefore be used in models for predicting maximal endurance times in complex cases. For the range of relative postural loads tested, an exponential function for predicting MET in static posture exertions produced the best fit curve.