Psychophysics is defined as the scientific study of the relationship between stimuli and sensation. It has been used extensively over the last three decades for evaluation and design of manual materials handling tasks in many industries. Despite this, much is still not known about how subjective ratings, the core of the psychophysical methodology, relate to physical (biomechanical) loads. A fundamental assumption of this method is that humans are capable of estimating biomechanical and physiological loads that are placed on the body. Based on this assumption, estimates that are obtained through the methodology are used as an indicator of physical loads and stresses, and are assumed to be related to injury risk. An experiment was performed to achieve two primary goals:1) determine the correspondence between biomechanical loads (moments at the elbow, shoulder and torso) and subjective ratings of joint loads, as well as subjectively determined maximal loads and 2) determine whether any particular joint (i.e. low back, shoulder, elbow) is the limiting factor when a subject determines a maximally acceptable load. Participants were instructed to pose in four different postures, one serving as a baseline (neutral, or 'familiar') posture, while the remaining three varied moments at the elbow, shoulder and torso. While in each of these postures, participants determined a maximum acceptable static load (MASL). Ratings of perceived exertions for specific joints were also reported, as well as whole body ratings while supporting various fractions of the MASL. Experimental findings indicated that subject and posture effects neared significance as main effects on the magnitude of MASL. Strength was shown to be, at best, a weak predictor of MASL. Though no conclusive evidence was found to indicate that a specific joint is the limiting factor when determining maximum acceptability, trends in the data suggested that the low back and shoulder are possible candidates. Overall, the results of the study indicated that humans consider more than simple joint moments when forming perceptions of efforts and acceptability during static load handling. / Master of Science

The Ergonomics Research Group at Queen’s University, supported by the Workplace and Safety Insurance Board, has been developing an on-line system to estimate peak and cumulative joint loading in the workplace. This study will aid the project by examining the muscle activation levels (MALs) in upper extremity and trunk muscles during a manual lifting task using both hands. It was hypothesized that MAL’s are correlated with the magnitude of the load in the hands and thus could be used to predict the load which in turn will be used to predict the lower back moments. Alterations in the muscle activation patterns due to lifting different loads were examined. Electromyographic signals (EMG) and kinematic data were recorded from different sites on the trunk and upper limb as subjects lifted a load from the floor to a shelf using squat, stoop and freestyle lift techniques. All raw EMG data were processed to obtain the linear envelopes (LE) which provides estimates of the MAL’s. The peak, mean and area of the linear envelopes were calculated. Using regression analysis, a relationship between the parameters and load lifted was found to exist. A non-linear parallel cascade type architecture was used to develop a model to predict the load in the hands. The model uses the EMG parameters as inputs and fits the data via linear and non-linear cascades to the output, i.e. the load in the hands. A model was successfully developed for the squat lift posture using the area, peak and mean of the zero-normalized EMG LE recorded from the erector spinae (L4 level), with a prediction error of ± 1.03kg and for the stoop posture, a prediction error of ± 2.34kg. Given the predicted loads, moments in the lower back were computed using the method of Hof (1992). / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2007-09-28 16:15:23.077

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