Classification of physical activities based on sparse representation.
This paper presents a new classification method for physical activity assessment, based on sparse representation. This method bypasses the need for feature extraction and selection that is typically involved for activity classification, and classifies activities using raw sensor signals directly. Higher discriminative power than that from the conventional k-nearest neighbor algorithm has been demonstrated through experiments performed on 105 subjects.
Electromechanical Systems Laboratory, Department of Mechanical Engineering, University of Connecticut, Storrs, CT 06269, USA.
Shaopeng
S
Liu
Robert X
RX
Gao
Dinesh
D
John
John
J
Staudenmayer
Patty S
PS
Freedson
D000465:Algorithms; D006801:Humans; D009043:Motor Activity