Accuracy of gait and posture classification using movement sensors in individuals with mobility impairment after stroke.

ABSTRACT: Background: Stroke leads to motor impairment which reduces physical activity, negatively affects social participation, and increases the risk of secondary cardiovascular events. Continuous monitoring of physical activity with motion sensors is promising to allow the prescription of tailored treatments in a timely manner. Accurate classification of gait activities and body posture is necessary to extract actionable information for outcome measures from unstructured motion data. We here develop and validate a solution for various sensor configurations specifically for a stroke population. Methods: Video and movement sensor data (locations: wrists, ankles, and chest) were collected from fourteen stroke survivors with motor impairment who performed real-life activities in their h

SUBMITTER: Pohl J 

PROVIDER: S-EPMC9549863 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature