Abstract:
Every year thousands of people fall prey to Parkinson’s disease, a neurodegenerative progressive disorder that slowly causes the loss of important neural motor functions in patients. Most of the Parkinson’s disease patients suffer from explicit hand tremors that cause uncontrollable shaking which they cannot control and often cause hindrances in their daily life activities. Many advancements have been made in the field of medicines and biotechnology to ease the tremors that occur in Parkinson’s disease patients but most have been proven either too expensive or simply do not cause enough relief in stabilizing the tremors. We present an innovative glove that helps patients in countering the hand tremors efficiently and cost effectively. The Tremor Ease glove equipped with accelerometer and gyroscope sensors, addresses the challenges posed by Parkinson’s related tremors. The sensors detect when a tremor occurs, and through the integration of machine learning into the microcontroller, a personalized threshold is set based on real-time hand movement data from these sensors. When this threshold is exceeded, a brushless DC motor with an added disc weight engages at a designated RPM, harnessing controlled inertia to suppress the tremors effectively.
