title: Classification of gait patterns in the time-frequency domain.
abstract: This paper describes the classification of gait patterns among descending stairs, ascending stairs and level walking activities using accelerometers arranged in antero-posterior and vertical direction on the shoulder of a garment. Gait patterns in continuous accelerometer records were classified in two steps. In the first step, direct spatial correlation of discrete dyadic wavelet coefficients was applied to separate the segments of gait patterns in the continuous accelerometer record. Compared to the reference system, averaged absolute error 0.387 s for ascending stairs and 0.404 s for descending stairs were achieved. The overall sensitivity and specificity of ascending stairs were 98.79% and 99.52%, and those of descending stairs were 97.35% and 99.62%. In the second step, powers of wavelet coefficients of 2 s time duration from separated segments of vertical and antero-posterior acceleration signals were used as features in classification. Our results proved a reliable technique of measuring gait patterns during physical activity.
authors.affiliation: Department of Mechanical Engineering, National University of Singapore, Singapore. engp2492@nus.edu.sg
authors.forename: M N
authors.initials: MN
authors.lastname: Nyan
authors.forename: F E H
authors.initials: FE
authors.lastname: Tay
authors.forename: K H W
authors.initials: KH
authors.lastname: Seah
authors.forename: Y Y
authors.initials: YY
authors.lastname: Sitoh
mesh_terms: D000054:Acceleration; D000328:Adult; D000465:Algorithms; D001696:Biomechanical Phenomena; D005260:Female; D005684:Gait / Q000502:physiology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D018670:Monitoring, Ambulatory / Q000295:instrumentation / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors; D016138:Walking / Q000145:classification / Q000502:physiology