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Proceedings of the 2023 Eighth International Conference on Research in Intelligent Computing in Engineering

Annals of Computer Science and Information Systems, Volume 38

Utilizing Flex Sensors for the Evaluation of Parkinson's Disease

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DOI: http://dx.doi.org/10.15439/2023R75

Citation: Proceedings of the 2023 Eighth International Conference on Research in Intelligent Computing in Engineering, Pradeep Kumar, Manuel Cardona, Vijender Kumar Solanki, Tran Duc Tan, Abdul Wahid (eds). ACSIS, Vol. 38, pages 115–120 ()

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Abstract. Parkinson's disease is a neurodegenerative disorder with symptoms such as tremors, stiffness, and issues with balance and coordination. Detecting and monitoring the signs of the disease is of great significance. By combining flex sensors and Arduino, we have designed a simple and effective system capable of recording, detecting, and evaluating early signs of the disease. The electronic components used are: an Arduino Nano, two flex sensors, and a glove with sensors attached to each finger to capture movements and flexion. The patient wears the glove and whenever tremors are detected, the sensor sends a signal to the Arduino which is converted into an angle of flexion by changing resistance. The tremor signals are initially transmitted as resistance and subsequently transformed into voltage. This voltage is then graphed according to the sensor's bending angle. By analyzing abrupt and rapid tremors, a threshold is established to deduce the severity and progression stage of the illness.

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