Abstract Summary
A feature selection method has been developed to characterize individual performance of locomotor activities of daily living. The method has been applied to angular and inertial data recorded with a novel 3D printed wearable device. Feature selection optimization through systematic removal of features improved classifier accuracy when applied to test data.
Sign in to ORCID