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<p>A model to predict carpal tunnel syndrome (CTS) risk would improve ergonomic assessments and help reduce the incidence of occupational CTS and its associated costs. Research spanning over sixty years has shown that deviated wrist, forearm, and hand posture has on the hydrostatic pressure within the carpal tunnel (also known as carpal tunnel pressure, CTP). Elevated CTP is a mechanism of the development, or aggravation of CTS symptoms. The purpose of this thesis was to develop a model to predict CTS risk, based on CTP, and incorporate the model into an ergonomic tool for use by ergonomists. An extensive literature review identified additional studies that investigated the effects of pronation/supination, finger posture, and fingertip loading on CTP. The effect of wrist, forearm, and hand posture was then incorporated into the model via a series of regression equations developed for each plane of movement. The effect of fingertip loading (independent to the posture effects) was included using a multiplier based on the hand posture and load magnitude. To provide a user-friendly tool for ergonomists, a graphical-user-interface was developed to predict CTS risk based on the developed model. Input variables were wrist, hand, and forearm posture, and fingertip loading. CTP program estimated CTP, and compared the predicted pressure to a known threshold beyond which median nerve function has been shown to degrade. The tool was then evaluated by comparing the output of the tool (CTS risk) to the incidence of CTS in a large automotive manufacturing environment. There was no significant difference between the two groups (workers completing jobs with an incidence of CTS and workers completing jobs with no incidence of CTS). The tool marks an important first step v towards providing ergonomists with a much-needed tool to predict CTS risk based on posture, frequency, and fingertip force.</p> / Master of Science (MSc)

<p>The primary purpose of this thesis was to measure arm strengths, in combinations of exertion directions, and to evaluate the importance of knowing the precise posture of the arm and specific joint locations in 3D space when predicting female arm strength. A stepwise multiple regression approach was utilized in the prediction of female arm strengths, using kinematic measures of hand location, arm posture and 26-force directions from 17 subjects and 8 hand locations as inputs. When including measures of arm posture, the regression model was indeed improved, explaining 75.4% of the variance, with an RMS error of 9.1 N, compared to an explained variance of 67.3% and an RMS error of 10.5 N without those postural variables. A comparison was also made between the empirical strength data from this thesis and the outputs from the University of Michigan’s Center for Ergonomics 3-Dimensional Static Strength Prediction Program (3DSSPP) software. A poor correlation (R-square = 0.305) and high RMS error (39 N) was found, indicating a definite need for further evaluation of the 3DSSPP package, as it is one of the most commonly used ergonomic tools in industry. <strong> </strong></p> / Master of Science (MSc)

<p>Few studies have shown the process of adaptation in muscle activity and joint angle during prolonged repetitive work. Fifteen healthy men performed 1 minute cycles of automotive-related tasks, which included a finger pull, knob turn, drill press and hose connector push. The experiment occurred on two days, separated by 24 hours. Day 1 required 61 cycles, with 5 cycles on day 2. Electromyography and kinematics of the upper extremity were analyzed at 12-minute intervals. Time to complete work cycle decreased by 6.3 s at the end of day 1 and 5.3 s on day 2. Peak EMG decreased for triceps brachii (TB), anterior deltoid (AD) and infraspinatus (IN) during work cycle, TB (finger pull), biceps brachii (BB), TB, AD, middle deltoid (MD) and IN during the hose insertion task. Peak EMG increased for MD and IN during the drill task. Mean EMG decreased for MD (work cycle), BB (hose insertion) and AD (finger pull), while MD and IN increased (drill task) and upper trapezius increased during the work cycle. EMG COV decreased for TB, AD, posterior deltoid and IN during the work cycle, TB during the finger pull task and AD during the hose insertion task. COV increased for BB during the work cycle, AD during the finger pull and for BB and lower trapezius during the drill press. Peak shoulder flexion decreased by 7.0° during the work cycle. Perceived discomfort increased by 1.2 units. This thesis found adaptations to highly repetitive but light work in only one hour, some of these changes persisted through the next day suggesting an adaptive process. This thesis is one of the first to examine adaptations to a highly repetitive simulated assembly work and has provided new insights into the evaluation of repetitive jobs as a whole and as isolated subtasks.</p> / Master of Science in Kinesiology