Repetitive stress injuries are common in the workplace where workers perform repetitive tasks continuously throughout the day. Muscle fatigue may lead to injury either directly through muscle damage or indirectly through changes in coordination, development of muscle imbalances, kinematic and muscle activation variability, and/or movement instability. To better understand the role of muscle fatigue in changes in movement parameters, we studied how muscle fatigue and muscle imbalances affected the control of movement timing, variability, and stability during a repetitive upper extremity sawing task. Since muscle fatigue leads to delayed muscle and cognitive response times, we might expect the ability to maintain movement timing would decline with muscle fatigue. We compared timing errors pre- and post-fatigue as subjects performed this repetitive sawing task synchronized with a metronome using standard techniques and a goal-equivalent manifold (GEM) approach. No differences in basic performance parameters were found. Significant decreases in the temporal correlations of the timing errors and velocities indicated that subjects made more frequent corrections to their movements post-fatigue. Muscle fatigue may lead to movement instability through a variety of mechanisms including delayed muscle response times and muscle imbalances. To measure movement stability, we must first define a state space that describes the movement. We compared a variety of different state space definitions and found that state spaces composed of angles and velocities with little redundant information provide the most consistent results. We then studied the affect of fatigue on the shoulder flexor muscles and general fatigue of the arm on movement stability. Subjects were able to maintain stability in spite of muscle fatigue, shoulder strength imbalance and decreased muscle cocontraction. Little is known about the time course for adaptations in response to fatigue. We studied the effect of muscle fatigue on movement coordination, kinematic variability and movement stability while subjects performed the same sawing task at two work heights. Increasing the height of the task caused subjects to make more adjustments to their movement patterns in response to muscle fatigue. Subjects also exhibited some increases in kinematic variability at the shoulder but no changes in movement stability. These findings suggest that people alter their kinematic patterns in response to fatigue possibly to maintain stability at the expense of increased variability. / text

Motor noise and redundancy are vexing issues in motor control; yet their understanding provides great insights on underlying control mechanisms that govern movement. They provide glimpses into how the nervous system organizes and regulates movement within the motor control system. Understand of motor control could spur new advances in motor control could lead to better development of rehabilitation process and technology to counteract debilitating affects of neuromuscular disorders and motor readjustment with prostheses. However, before such process and technology could be developed and adapted for clinical use, a deeper understanding of motor control is needed to unravel the neural roadmap that regulates and generates movement. New theory of motor control could precipitate the development of more robust control mechanisms for robotic-human interaction. This work aims at expanding a more rigorous analytical and mathematical framework to understand how these control mechanisms reconcile redundancy and stochastic noise in human motor control. / text

Trial-to-trial variability in human movement is often overlooked and averaged out, but useful information can be gleaned on the brain’s control of variability. A task can be defined by a function specifying a solution manifold along which all task variable combinations will lead to goal success – the Goal-Equivalent Manifold (GEM). We selected a reaching task with variables reach Distance (D) and reach Time (T). Two GEMs were selected: a constant D/T and constant D×T. Subjects had no knowledge of the goal prior to the experiments and were instructed only to minimize error. Subjects learned the generalized tasks by reducing errors and consolidated learning from one day to the next, generalized learning from the D×T to the D/T GEM, and had interference of learning from the D/T to the D×T GEM. Variability was structured along each GEM significantly more than perpendicular to it. Deviations resulting in errors were corrected significantly more quickly than any other deviation. Our results indicate that subjects can learn generalized reaching tasks, and the brain exploits redundancy in those tasks. / text

The human body has substantial kinetic and kinematic degrees-of-freedoms, so redundant solutions are available for the central nervous system (CNS) to perform a repetitive task. Due to these redundancies, inherent variations exist in human movement, called motor variability (MV). Current evidence suggests that MV can be beneficial, and that there is an inverse association between MV and risk of injury. To better understand how the CNS manipulates MV to reduce injury risks, we investigated the effects of individual differences, task-relevant aspects, and psychological factors as modifiers of MV. Earlier work found that experienced workers adapted more stable movements than novices in repetitive lifting tasks. To expand on this, we quantified how MV differs between experienced workers and novices in different lifting conditions (i.e., lifting asymmetry and fatigue). Three different measures (cycle-to-cycle SD, sample entropy, and the goal equivalent manifold) were used to quantify MV. In a symmetric lifting task, experienced workers had more constrained movement than novices, and experienced workers exhibited more consistent behavior in the asymmetric condition. Novices constrained their movements, and could not maintain the same level of variability in the asymmetric condition. We concluded that experienced workers adapt stable or flexible strategies depending on task difficulty. In a prolonged lifting task, both groups increased their MV to adapt to fatigue; they particularly increased variability in a direction that had no effects on their main task goal. Developing fatigue also makes it difficult for individuals maintain the main goal. Based on these results, we conclude that increasing variability is an adaptive strategy in response to fatigue. We also assessed variability in gait parameters to compare gait adaptability using a head-worn display (HWD) compared with head-down displays for visual information presentation. An effective strategy we observed for performing a cognitive task successfully during walking was to increase gait variability in the goal direction. In addition, we found that head-up walking had smaller effects on MV, suggesting that HWDs are a promising technology to reduce adverse events during gait (e.g., falls). In summary, these results suggest that MV can be a useful indicator for evaluating some occupational injury risks. / Ph. D. / Whenever an individual performs a repetitive task, we can observe variations in their movement patterns. The magnitude of these variations, which are called motor variability, may be related to the risk of injury. To better understand this relationships, we investigated how different risk factors affect the patterns of human movement. In two studies, we compared movement patterns of experienced workers and novices in a repetitive lifting task. In a simple, brief lifting task, novices had more variations in their movement patterns. However, novices did not have the same level of variation in asymmetric lifting tasks, and constrained their movement more than experienced workers. Experienced workers, though, had a similar level of variation in both simple and more difficult lifting conditions. We concluded that whether stable or flexible movement pattern are used depends on task difficulty and the level of experience. In a longer-duration lifting task, both experienced workers and novices increased variations in their movement patterns over time, and we believe that these increases were an adaptation to fatigue. In a third study, we investigated the differences between variations in walking pattern when people use different types of information display (i.e., paper, cellphone, and smart glasses). Using smart glasses had a smaller effect on movement patterns, suggesting that this technology is potentially is safer than other types of display. In summary, these results suggest that studying the variations in human movement patterns can be a useful indicator to evaluate the risk of injury.