Motor Functions Assessment for Parkinson Disease via Radar Sensors Focusing on Finger Tapping Test

Abstract

Abstract This thesis investigates the assessment of motor functions using a radar sensor, focusing on the finger tapping test. The primary goal is to help healthcare professionals in accurately detecting and analyzing finger tapping test, which is essential for effective treatment and management of Parkinson’s disease (PD). Data of several finger tapping scenarios was collected by mimicking them by healthy individuals using the radar sensor, followed by comprehensive data and signal processing. The developed model achieved a promising accuracy of 93.18% on the dataset collected by students. It successfully identified and scored the cases with interruptions, as well as amplitude and frequency decrements, although it does not provide a severity score for decrement cases. However, the model’s inability to handle cases involving combinations of interruptions and decrements was identified as a limitation. Tests conducted by physiotherapists resulted in lower accuracy, primarily due to the radar sensor’s high sensitivity to motion and distance changes. This thesis explores the potential of radar sensor technology in monitoring motor functions while highlighting the challenges associated with data collection and sensor sensitivity.