title: Key joint kinematic characteristics of the gait of fallers identified by principal component analysis.
abstract: It has been reported that fallers have a higher risk of subsequent falls than non-fallers. Therefore, if the differences between the movements of recent fallers and non-fallers can be identified, such could be regarded as the basis of the high risk of falling of the former. The objective of the present study was the identification of the key joint kinematic characteristics of human gait related to the risk of falling while walking on level ground. For this purpose, joint kinematics data obtained from 18 recent fallers and 19 non-fallers were analyzed using principal component analysis (PCA). The PCA was conducted using an input matrix constructed from the time-normalized average and standard deviation of the lower limb joint angles on three planes (101 data×2 parameters×3 angles×3 planes). The PCA revealed that only the 5th principal component vector (PCV 5) among the 23 generated PCVs was related to the risk of falling (p<0.05, ES=0.71). These findings as well as those of previous studies suggest that the joint kinematics of PCV 5 is the key characteristic that affects the risk of falling while walking. We therefore recombined the joint kinematics corresponding to PCV 5 and concluded that the variability of the joint kinematics for fallers was larger than that for non-fallers regardless of the joint. These observations as well as the findings of previous studies suggest that the risk of falling can be reduced by reducing the variability of the joint kinematics using an intervention such as external cues or a special garment.
authors.affiliation: Digital Human Research Center, National Institute of Advanced Industrial Science and Technology, 2-8-5 Aomi, Koto-ku, Tokyo 135-0064, Japan. Electronic address: kobayashi-yoshiyuki@aist.go.jp.
authors.forename: Yoshiyuki
authors.initials: Y
authors.lastname: Kobayashi
authors.affiliation: Digital Human Research Center, National Institute of Advanced Industrial Science and Technology, 2-8-5 Aomi, Koto-ku, Tokyo 135-0064, Japan.
authors.forename: Hiroaki
authors.initials: H
authors.lastname: Hobara
authors.affiliation: Digital Human Research Center, National Institute of Advanced Industrial Science and Technology, 2-8-5 Aomi, Koto-ku, Tokyo 135-0064, Japan.
authors.forename: Shiho
authors.initials: S
authors.lastname: Matsushita
authors.affiliation: Digital Human Research Center, National Institute of Advanced Industrial Science and Technology, 2-8-5 Aomi, Koto-ku, Tokyo 135-0064, Japan.
authors.forename: Masaaki
authors.initials: M
authors.lastname: Mochimaru
mesh_terms: D000058:Accidental Falls / Q000517:prevention & control*; D000368:Aged; D001696:Biomechanical Phenomena; D005260:Female; D005684:Gait / Q000502:physiology*; D006801:Humans; D007596:Joints / Q000502:physiology*; D008297:Male; D008875:Middle Aged; D009068:Movement; D025341:Principal Component Analysis; D012306:Risk; D016138:Walking
keywords: Fallers and non-fallers; Falling; Gait; Joint kinematics; Principal component analysis