Assigning UPDRS Scores in the Leg Agility Task of Parkinsonians: Can It Be Done through BSN-based Kinematic Variables?

TL;DR

This study explores using body-worn sensors to automatically estimate Parkinson's disease severity scores during a leg agility task, aiming for a portable IoT-compatible assessment tool.

Contribution

It introduces a method linking kinematic variables from inertial sensors to UPDRS scores, advancing automatic PD severity assessment.

Findings

Kinematic variables correlate with UPDRS scores.

Feasibility of portable sensor-based assessment demonstrated.

Potential for IoT integration in PD monitoring.

Abstract

In this paper, by characterizing the Leg Agility (LA) task, which contributes to the evaluation of the degree of severity of the Parkinson's Disease (PD), through kinematic variables (including the angular amplitude and speed of thighs' motion), we investigate the link between these variables and Unified Parkinson's Disease Rating Scale (UPDRS) scores. Our investigation relies on the use of a few body-worn wireless inertial nodes and represents a first step in the design of a portable system, amenable to be integrated in Internet of Things (IoT) scenarios, for automatic detection of the degree of severity (in terms of UPDRS score) of PD. The experimental investigation is carried out considering 24 PD patients.