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Journal Articles Sensors Year : 2022

Scoring the Sit-to-Stand Performance of Parkinson’s Patients with a Single Wearable Sensor

Abstract

Monitoring disease progression in Parkinson’s disease is challenging. Postural transfers by sit-to-stand motions are adapted to trace the motor performance of subjects. Wearable sensors such as inertial measurement units allow for monitoring motion performance. We propose quantifying the sit-to-stand performance based on two scores compiling kinematics, dynamics, and energy-related variables. Three groups participated in this research: asymptomatic young participants (n = 33), senior asymptomatic participants (n = 17), and Parkinson’s patients (n = 20). An unsupervised classification was performed of the two scores to differentiate the three populations. We found a sensitivity of 0.4 and a specificity of 0.96 to distinguish Parkinson’s patients from asymptomatic subjects. In addition, seven Parkinson’s patients performed the sit-to-stand task “ON” and “OFF” medication, and we noted the scores improved with the patients’ medication states (MDS-UPDRS III scores). Our investigation revealed that Parkinson’s patients demonstrate a wide spectrum of mobility variations, and while one inertial measurement unit can quantify the sit-to-stand performance, differentiating between PD patients and healthy adults and distinguishing between “ON” and “OFF” periods in PD patients is still challenging.

Dates and versions

hal-03846977 , version 1 (10-11-2022)

Identifiers

Cite

Frédéric Marin, Elke Warmerdam, Zoé Marin, Khalil Ben Mansour, Walter Maetzler, et al.. Scoring the Sit-to-Stand Performance of Parkinson’s Patients with a Single Wearable Sensor. Sensors, 2022, 22 (21), pp.8340. ⟨10.3390/s22218340⟩. ⟨hal-03846977⟩
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