Association Rule Mining to Examine Predictors for the Outcome of Gait Rehabilitation Programs in Stroke Survivors.

ABSTRACT:

Abstract

This study presents a novel application of association rule data mining to determine the predictors of the response to locomotor training and home exercise for improving gait after stroke. The study was a secondary data analysis on the Locomotor Experience Applied Post Stroke Trial dataset. The association rule analysis was applied to analyze three interventions: (1) early locomotor training, (2) late locomotor training, and (3) home exercise program. The outcome variable was whether participants poststroke had greater than median improvement in the self-selected comfortable gait speed. Three types of predictors were investigated: (1) demographics, (2) behavioral and medical history, and (3) clinical assessments at baseline. Association rules were generated when they meet

SUBMITTER: Yen SC 

PROVIDER: S-EPMC9018884 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature