Modeling of shoulder and torso effort perception in manual tasks

While biomechanical motion simulation models attempt to predict body segment movements in space and muscle forces, it is still necessary to develop models predicting the subjective perception of effort, as it represents an integration of the physical demand of the task. The aim of the present study was to develop statistical models of perceived effort at the shoulder and torso levels associated with load manipulation using one or both hands. The motions were directed from a home location toward one of twenty-two target shelves distributed around the subjects. The perception of effort at the shoulder and the low back area was rated using a ten-point visual analog scale. Calibration of perception was carried out by training each subject using a set of predetermined effort levels expressed as 6 percentage of their maximum voluntary shoulder flexion and torso extension, respectively. A total of 3,210 ratings were obtained from thirty-one subjects. A logit transformation of the response variables was performed to bound,the predictions within the finite range of the scale and take into account that effort perception is generally described by a power function. Then, both stepwise and standard least square regression methods were used to identify significant factorial effects and their corresponding coefficients. The regression models include input parameters such as standing or seated posture, one or two handed transfer, target position, demographic and anthropometric measures, and torso or shoulder maximum strength levels. The resulting models provide a fairly good prediction of effort perception with r-square coefficients of .66 and .60 for the shoulder and torso, respectively. Such models can be used to optimize the workspace and minimize work related musculoskeletal disorders.