title: Age-independent and age-dependent sex differences in gait pattern determined by principal component analysis.
abstract: Although various studies have reported significant sex differences in pelvic and/or hip-joint motion during normal walking in healthy adults, it is still unclear whether such differences are among the most dominant age-independent sex differences. This study was conducted to analyze the whole waveform of lower-extremity joint kinematics obtained from 191 healthy adults using a principal component analysis (PCA). The PCA was conducted using a 955×1212 input matrix constructed from the participants' time-normalized pelvic and right-lower-limb-joint angles along three axes (five trials of 191 participants×101 data points×4 angles×3 axes). Two-way (age×sex) analyses of variance were conducted on the principal component scores (PCSs) of principal component vectors (PCVs) 1 through 6, each of which explained more than 5% of the variance. We identified a PCV that exhibits a significant age-sex interaction (PCV 1). The characteristics of sex differences reported in previous studies could be observed in the reconstructed waveforms of this PCV. Thus, we can conclude that the sex differences in the gaits reported in previous studies are not consistent across age groups. Furthermore, we also found a PCV that exhibited only a significant sex difference (PCV 6). This PCV was the first and only PCV to exhibit a sex difference without any age-related effect or age-sex interaction. Therefore, we concluded that the movement related to this PCV is age-independent and is the most dominant sex difference in the gaits observed during normal walking.
authors.affiliation: Digital Human Research Group, Human Informatics Research Institute, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan. Electronic address: kobayashi-yoshiyuki@aist.go.jp.
authors.forename: Yoshiyuki
authors.initials: Y
authors.lastname: Kobayashi
authors.affiliation: Digital Human Research Group, Human Informatics Research Institute, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan.
authors.forename: Hiroaki
authors.initials: H
authors.lastname: Hobara
authors.affiliation: Digital Human Research Group, Human Informatics Research Institute, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan.
authors.forename: Thijs A
authors.initials: TA
authors.lastname: Heldoorn
authors.affiliation: Digital Human Research Group, Human Informatics Research Institute, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan.
authors.forename: Makiko
authors.initials: M
authors.lastname: Kouchi
authors.affiliation: Digital Human Research Group, Human Informatics Research Institute, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan.
authors.forename: Masaaki
authors.initials: M
authors.lastname: Mochimaru
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D001696:Biomechanical Phenomena; D005260:Female; D005684:Gait / Q000502:physiology*; D006801:Humans; D035002:Lower Extremity / Q000502:physiology*; D008297:Male; D008875:Middle Aged; D010388:Pelvis / Q000502:physiology*; D025341:Principal Component Analysis; D012737:Sex Factors; D016138:Walking / Q000502:physiology*
keywords: Age; Gait; Joint kinematics; Principal component analysis; Sex