Muscular performance modeling of the upper limb in static postures

The purpose of the present paper is to describe and evaluate the polynomial models for predicting the muscular work capacity of the upper limb during sustained holding tasks. This research was concerned with the relationship between indicators of performance, i.e., specific posture or specific level of maximum voluntary contraction (MVC), and then modeling the functional data based on experimental results to estimate factors that may have an effect on task performance. To this end, we designed an experiment using 10 subjects in which each subject performed sustained isometric shoulder and elbow flexion endurance exercise under 27 conditions [3 shoulder angles (SA)x3 elbow angles (EA)x3 levels of %MVC]. Throughout all experiments, subjective perception of effort was assessed using the Borg scale, every 60, 30, and 10 s during the 20%, 40%, and 60% MVC tests, respectively. Proposal models were represented by three approaches: model A: estimation of endurance time (ET), with input variables such as SA, EA, and %MVC; model B: estimation of recommendation time (RT, the time during which the operator was able to maintain a position under the desired condition), with input variables such as SA, EA, %MVC, and required rate on the Borg scale; and model C: estimation of limit strength or %MVC, with input variables such as SA, EA, request limit time for work (LT), and required rate on the Borg scale. Statistical analysis indicated that the three proposal estimation models based on polynomial regression functions showed high significance (p<0.0001). The proposal models suggested and recommended the possibility of finding the best positions entailing the reduction and minimization of total muscular strain from manual material handling tasks in different work situations, with the consequent increase in work efficiency.