Gait video-based prediction of unified Parkinson's disease rating scale score: a retrospective study.

ABSTRACT:

Background

The diagnosis of Parkinson's disease (PD) and evaluation of its symptoms require in-person clinical examination. Remote evaluation of PD symptoms is desirable, especially during a pandemic such as the coronavirus disease 2019 pandemic. One potential method to remotely evaluate PD motor impairments is video-based analysis. In this study, we aimed to assess the feasibility of predicting the Unified Parkinson's Disease Rating Scale (UPDRS) score from gait videos using a convolutional neural network (CNN) model.

Methods

We retrospectively obtained 737 consecutive gait videos of 74 patients with PD and their corresponding neurologist-rated UPDRS scores. We utilized a CNN model for predicting the total UPDRS part III score and four subscores of axial symptoms (items 27,

SUBMITTER: Eguchi K 

PROVIDER: S-EPMC10552271 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature