title: Classifying human motion quality for knee osteoarthritis using accelerometers.
abstract: In this paper, we describe methods for assessment of exercise quality using body-worn tri-axial accelerometers. We assess exercise quality by building a classifier that labels incorrect exercises. The incorrect performances are divided into a number of classes of errors as defined by a physical therapist. We focus on exercises commonly prescribed for knee osteoarthritis: standing hamstring curl, reverse hip abduction, and lying straight leg raise. The methods presented here will form the basis for an at-home rehabilitation device that will recognize errors in patient exercise performance, provide appropriate feedback on the performance, and motivate the patient to continue the prescribed regimen.
authors.affiliation: Biomedical Engineering Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA. pet@cs.cmu.edu
authors.forename: Portia E
authors.initials: PE
authors.lastname: Taylor
authors.forename: Gustavo J M
authors.initials: GJ
authors.lastname: Almeida
authors.forename: Takeo
authors.initials: T
authors.lastname: Kanade
authors.forename: Jessica K
authors.initials: JK
authors.lastname: Hodgins
mesh_terms: D000054:Acceleration; D000203:Activities of Daily Living / Q000145:classification*; D000465:Algorithms; D005081:Exercise Therapy / Q000295:instrumentation / Q000379:methods*; D005260:Female; D057918:Fiducial Markers; D006801:Humans; D008297:Male; D009068:Movement / Q000502:physiology*; D020370:Osteoarthritis, Knee / Q000534:rehabilitation*; D015203:Reproducibility of Results