Data-Driven Models for Objective Grading Improvement of Parkinson's Disease.

ABSTRACT: Parkinson's disease (PD) is a progressive disorder of the central nervous system that causes motor dysfunctions in affected patients. Objective assessment of symptoms can support neurologists in fine evaluations, improving patients' quality of care. Herein, this study aimed to develop data-driven models based on regression algorithms to investigate the potential of kinematic features to predict PD severity levels. Sixty-four patients with PD (PwPD) and 50 healthy subjects of control (HC) were asked to perform 13 motor tasks from the MDS-UPDRS III while wearing wearable inertial sensors. Simultaneously, the clinician provided the evaluation of the tasks based on the MDS-UPDRS scores. One hundred-ninety kinematic features were extracted from the inertial motor data. Data processing and stati

SUBMITTER: Butt AH 

PROVIDER: S-EPMC7723941 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature