Classification of Parkinson's disease with freezing of gait based on 360° turning analysis using 36 kinematic features.

ABSTRACT:

Background

Freezing of gait (FOG) is a sensitive problem, which is caused by motor control deficits and requires greater attention during postural transitions such as turning in people with Parkinson's disease (PD). However, the turning characteristics have not yet been extensively investigated to distinguish between people with PD with and without FOG (freezers and non-freezers) based on full-body kinematic analysis during the turning task. The objectives of this study were to identify the machine learning model that best classifies people with PD and freezers and reveal the associations between clinical characteristics and turning features based on feature selection through stepwise regression.

Methods

The study recruited 77 people with PD (31 freezers and 46 non-freezers)

SUBMITTER: Park H 

PROVIDER: S-EPMC8686361 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature