NeuroSense: Early Detection for Parkinson’s Diseases

Parkinson’s Disease (PD) is a progressive neurological disease that affects movement, coordination, and motor control. Early detection of Parkinson’s disease is critical for better patient management and slowing the progress of the disease. According to various global health reports, Parkinson’s disease affects millions of people worldwide and the prevalence of Parkinson’s disease increases with age [2][3]. In this paper, the authors propose a multimodal Parkinson’s disease detection system using Electromyography (EMG) and Inertial Measurement Unit (IMU) sensors. The proposed system collects physiological and movement information from the patients using the sensors and detects the early symptoms of Parkinson’s disease. The proposed system uses the classification of the sensor information using the machine learning algorithm for the detection of Parkinson’s disease. The proposed system uses the combination of the sensors for the detection of Parkinson’s disease. The experimental analysis proves the effectiveness of the proposed system for the detection of Parkinson’s disease using the sensors. The proposed system is useful for the doctors in the detection of Parkinson’s disease patients, which is the contribution of the proposed system.