Yun Qin, Naila Rahman and Farshid Amirabdollahian
In the context of therapeutic human-robot interaction, it is important to detect human contribution in interaction with robots, thus to auto-tune a robot to compensate or resist based on such input. A passive orthosis is used to evaluate interaction based on kinematic data and energy flow model to identify human-contributions during interaction experiments with healthy subject and stroke patient. The results identified presence of abnormal synergies between wrist and fingers, showed a skewness apparent in stroke patient performance which seemed to decrease over-time after the rehabilitation practice and indicated lack of fine control. We hypothesise that the presented methods can be used as potential performance benchmarks allowing to identify subject’s contribution during an interaction session but also to observe extent of fine motor control over time.
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