Human adaptation to augmented reality-based hand rehabilitation technique

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Venkata Naga Alekhya, Sajja
Desai, Jaydip M.

Stroke is the number one cause of motor impairment in multiple countries [1]. The demand and affordability of physiotherapy are factors that prevent access to rehabilitation. Modern technology has found a successful solution in terms of robotic exoskeletons for motor impairment and augmented reality for motivation. But often, a stroke survivor needs motor rehabilitation and motivation to work hand in hand to ensure the quality of rehabilitation. The objective of this thesis was to study the human adaptability to augmented reality (AR) and pneumatic soft robotic glove-based rehabilitation system by recording human subjects’ response during four repetitive activities of daily living (ADL) tasks done using four game objects in an AR environment (A bottle, spoon, fidget spinner and slider) in three different modes of assistance. The results were depicted in terms of 1. task response which shows that mode 1 has the highest mean percentage response of (98.3%) which indicates that subjects can adapt to augmented reality at ease, mode 2 and mode 3 have the low mean percentage response (78.4%, 46.7%) indicating that the hand tracking system needs to improve in terms of detecting soft robotic glove actuators, object bottle had most task response (90%) and object spoon had the least task response (45.%) indicating subject adaptation to pick and place task is higher than pinch and rotate tasks, 2. response trajectory showed that the subjects at majority, performed the tasks as instructed. 3. time taken for task completion was highest at mode 1 and lowest at mode 3 indicating the soft robotic there is system caused a delay as the modes progress. 4. minimum/maximum distance achieved by subjects depicts the interaction of each subject with respect to task and mode.

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Thesis (M.S.)-- Wichita State University, College of Engineering, Dept. of Biomedical Engineering