Effect of internal model development on effort and error during EMG control of three functional tracking tasks

Powered upper limb prostheses typically use EMG to control movement. EMG control is often variable and inefficient, and it is unclear if persons benefit from use of internal models, which have been shown to improve performance with traditional human-machine interfaces. We investigated how internal model use affected errors and effort across a group of 20 subjects using EMG control to perform a tracking task. To vary the ability of subjects to form an internal model, we altered the amount of available information using three visual displays: compensatory, pursuit, and preview. Subjects were more accurate and exerted less effort with visual displays that provided more information and enabled stronger internal model formation (p<;0.01).