Evaluation of Postural Sway in Post-stroke Patients by Dynamic Time Warping Clustering.

ABSTRACT: Post-stroke complications are the second most frequent cause of death and the third leading cause of disability worldwide. The motor function of post-stroke patients is often assessed by measuring the postural sway in the patients during quiet standing, based on sway measures, such as sway area and velocity, which are obtained from temporal variations of the center of pressure. However, such approaches to establish a relationship between the sway measures and patients' demographic factors have hardly been successful (e.g., days after onset). This study instead evaluates the postural sway features of post-stroke patients using the clustering method of machine learning. First, we collected the stroke patients' multi-variable motion-capture standing-posture data and processed them into t</

SUBMITTER: Li D 

PROVIDER: S-EPMC8678529 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature