Detection of Parkinson’s Tremor in Real Time Using Accelerometers

Abstract

Parkinson’s illness is a neurodegenerative disorder that prompts shaking, firmness, and trouble with strolling, equilibrium, and coordination. Detection of Parkinson disease (PD) is of sublime importance at entry stage. At later stages, the disease can quickly amplify tremor and makes aging in place difficult for patient. Less than 5% patient get this detection in time because of complex testing procedures and cost factor [6]. Objective of this research is to use a general-purpose economical accelerometer to collect data of PD patients and analyses it in real time for the detection of PD. Integration of open-source microcontroller along with the modern accelerometer to get the sensing results. We likewise contrast distinctive accelerometer with check, which one is better, and give us exact outcomes. On top of that, we simulated our results in MATAB. ADXL335 and MPU-6050 were used in this research project. System works well and predicts the PD in patients. Amplitude of tremor signal and post signal processing determine the intensity of PD. MPU-6050 however shows better results in predicting the stage of Parkinson.