Cerebral Palsy (CP)is a collection of permanent, non-progressive disorders that impact the individual’s motor ability. The rehabilitation of patients with CP is very important to improve their motor abilities and to minimize the need for third parties. In this paper, a low-cost hand rehabilitation glove based on finger bend/pressure analysis is presented. The data glove is used to improve hand functioning for pre-school children with cerebral palsy through virtual reality games. The system consists of two parts: the data glove and several virtual games. The data glove consists of a microcontrol-ler, flex sensors, force sensors and radiofrequency transmission units. The use of the newly developed system will assist psychotherapist to follow the CP child daily, weekly or monthly. The rehabilitation model and the predicted physiotherapy results can be extracted from the patient’s record after using the data. Experimental results have shown that the regular usage for the data glove improved 75 % of the participants’ fingers bending angel and the child’s grip ability.
Development of a Low-cost Data Glove using Flex Sensors for the Robot Hand Teleoperation