Wearable Sensor-Based Estimation of Leg Agility Amplitude for Objective Assessment in Parkinson’s Disease

Parkinson's disease (PD) is a progressive neurodegenerative disorder that significantly affects motor function. In clinical practice, symptom severity is typically assessed through subjective evaluation. The Movement Disorder Society - Unified Parkinson's Disease Rating Scale includes the Leg Agility test to assess lower limb bradykinesia, traditionally evaluated through visual observation. Objective evaluation methods are still not commonly used. To enhance accuracy and reproducibility, this work proposes an inertial measurement unit (IMU)-based algorithm for estimating the amplitude during the Leg Agility test. Our method processes acceleration and angular velocity signals from IMUs placed on the foot and thigh and compares them to determine optimal sensor placement. Validation was conducted using a motion capture system as ground truth. The results demonstrate that the thigh-mounted sensor yields superior accuracy, with a median root mean square error of 1.08 cm for the thigh and 1.84 cm for the foot, and a mean absolute peak error of 0.96 cm and 2 cm, respectively. Our algorithm shows good performance in capturing amplitude trends, a key factor in clinical assessment of the Leg Agility test. These findings support the feasibility of IMU-based monitoring for objective PD symptom assessment, offering a practical and objective alternative to traditional methods.