Feature selection for elderly faller classification based on wearable sensors.
Journal:
Journal of neuroengineering and rehabilitation
Published Date:
May 30, 2017
Abstract
BACKGROUND: Wearable sensors can be used to derive numerous gait pattern features for elderly fall risk and faller classification; however, an appropriate feature set is required to avoid high computational costs and the inclusion of irrelevant features. The objectives of this study were to identify and evaluate smaller feature sets for faller classification from large feature sets derived from wearable accelerometer and pressure-sensing insole gait data.
