Intelligent System using Flex Sensor for the Assessment of Parkinson's Disease

Parkinson’s disease is a progressive nervous system disorder that affects movement which is prevalent in a large number of the world’s population and progressively deteriorates over time. A prognostic system using flex sensors was used to detect tremors in people to assess the severity, progression and chances of regression of the disease. The electronic components used are: an Arduino Nano, five novel flex sensors made of a carbon material known as velostat and a glove onto which the sensors are attached at each finger to record movements and bending. The glove is worn by the patient and every time a tremor is detected; sensors send signals to the Arduino which are converted to bend angles using the change in resistance. The tremor signals are sent in the form of resistances and then converted to voltage. The voltage is then plotted as a function of the bend angle of the flex sensor. A threshold was determined using the sudden and rapid tremors, causing a change in resistance from which the severity and stage of Parkinson’s in the patient can be inferred. This system can be useful for patients who have come out of therapy but still have recurring symptoms.