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Machine Learning based Hand Orthotic Device

School: School of Engineering

Project Incharge:Dr. Rajesh Kannan
Machine Learning based Hand Orthotic Device

Robotic systems are rapidly emerging as easy-to-use rehabilitation tools that enhance several of health-related infirmities. Frequently, stroke and spinal cord -injuries are impair normal healthful living by paralysis, albeit the affected patient’s brains may remain functional. Such victims need long-term rehabilitation, by qualified therapists to regain motor and sensory controls, beyond the affordable reach of common citizens. This is where reasonably priced robotic exoskeleton systems come to their rescue. we are using a novel design for hand orthosis, which is a lightweight pliable prototype and is been calibrated to fit any average-sized hand. This device is controlled with a voice recognition module, IOT and Bluetooth. Our device can be used for picking up the objects and give an extra grasp to the patients. Empirical results validate the efficacy, reliability, and robustness of the orthotic device that can be used in the rehabilitation of stroke patients.

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