Interpretable classification for multivariate gait analysis of cerebral palsy.

ABSTRACT:

Background

The Gross Motor Function Classification System (GMFCS) is a widely used tool for assessing the mobility of people with Cerebral Palsy (CP). It classifies patients into different levels based on their gross motor function and its level is typically determined through visual evaluation by a trained expert. Although gait analysis is commonly used in CP research, the functional aspects of gait patterns has yet to be fully exploited. By utilizing the gait patterns to predict GMFCS, we can gain a more comprehensive understanding of how CP affects mobility and develop more effective interventions for CP patients.

Result

In this study, we propose a multivariate functional classification method to examine the relationship between kinematic gait measures and GMFCS levels in

SUBMITTER: Yoon C 

PROVIDER: S-EPMC10664661 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature