Posture and control based mechanisms of upper extremity disorders

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Over the past few decades, great advances have been made in the understanding human movement and how disabilities impede normal function. There is a great need to fully understand the mechanisms by which the human upper extremity (shoulder, arm, and hand) becomes injured with everyday use. These disorders involve muscle tissue (muscle pain), connective tissue (e.g. tennis elbow), and peripheral nerves (e.g. carpal tunnel syndrome). By understanding the control of movement and the way muscle, tendon and ligament forces interact inside the arm, we can ultimately prevent disorders, especially those developed at work. Unlike injuries to the lower back, disorders of the upper extremity tend to occur over time and cannot be attributed to a specific event, thus the mechanical origins of upper extremity injuries are elusive. Studies indicate that loads, postures and motion are highly linked to injury risk. Compensatory strategies to control the hand, arm and shoulder muscles may indicate which individuals are susceptible to greater individual muscle loading, fatigue and injury. My research program methodically investigates the effects of muscular loading by monitoring arm movement, muscle activity and their interactions with computer-based modeling. We use magnetic resonance imaging (MRI) and ultrasound to examine structural changes in the wrist in different wrist postures during pinching actions to determine mechanics of nerve compression in carpal tunnel syndrome. We also examine the activation patterns (timing and magnitude) of shoulder, arm and hand muscles to determine how muscles work to create movement in specific tasks. By doing studies such as these when people's muscles are fresh and when they are fatigued, we can determine the way people deal with tiring stereotypical movements like on an assembly line. A major part of this research program is to develop and improve the computer model to predict forces inside the arm and hand. By combining muscle activity and anatomical data in a computer model, we can test theories on how disorders develop and how to prevent them as well as ask "what would happen if ...?" questions that otherwise could not be answered ethically.