title: Measuring gait pattern in elderly individuals by using a plantar pressure measurement device.
abstract: BACKGROUND
  Hip fracture in the elderly is a serious problem, and solutions to prevent falls are needed.
  
  
  OBJECTIVE
  This study focused on elucidating data critical to fall prevention by evaluating ambulatory function, and we achieved this by developing a plantar pressure measurement device to determine gait function.
  
  
  METHODS
  Our device enables measurement of gait function in the unrestrained state by transmitting wireless data. In this study, we applied the device to field experiments involving 98 subjects (39 healthy individuals, 44 elderly non-fallers, and 15 elderly fallers). Gait features were determined by measuring the pressure values and foot contact patterns used as gait function parameters in previous studies.
  
  
  RESULTS
  In particular, decreased peak pressure values were noted at heel strike and toe off during walking in elderly fallers compared with elderly non-fallers. In addition, compared with healthy subjects, elderly fallers also showed extension of the double support phase, and differences in individual gait pattern features were observed between the groups.
  
  
  CONCLUSIONS
  Experiments confirmed that our device can be used to obtain the gait features of a diverse group of elderly individuals. Moreover, our device enables objective and quantitative evaluation of gait function and thus may be useful for evaluating gait function in the elderly.
authors.affiliation: Department of Human Life and Environmental Sciences, Graduate School of Humanities and Science, Ochanomizu University, Tokyo, Japan.
authors.forename: Kanako
authors.initials: K
authors.lastname: Nakajima
authors.affiliation: Department of Human Life and Environmental Sciences, Graduate School of Humanities and Science, Ochanomizu University, Tokyo, Japan.
authors.forename: Emi
authors.initials: E
authors.lastname: Anzai
authors.affiliation: Faculty of Healthcare, Division of Healthcare Informatics, Tokyo Healthcare University, Tokyo, Japan.
authors.forename: Yumi
authors.initials: Y
authors.lastname: Iwakami
authors.affiliation: Institute for Human Science and Biomedical Engineering, National Institute of Advanced Industrial Science and Technology, Ibaraki, Japan.
authors.forename: Shuichi
authors.initials: S
authors.lastname: Ino
authors.affiliation: Faculty of Healthcare, Division of Healthcare Informatics, Tokyo Healthcare University, Tokyo, Japan Division of Health Sciences, Graduate School of Medicine, Osaka University, Osaka, Japan.
authors.forename: Kazuhiko
authors.initials: K
authors.lastname: Yamashita
authors.affiliation: Department of Human Life and Environmental Sciences, Graduate School of Humanities and Science, Ochanomizu University, Tokyo, Japan.
authors.forename: Yuji
authors.initials: Y
authors.lastname: Ohta
mesh_terms: D000058:Accidental Falls / Q000517:prevention & control; D000368:Aged / Q000502:physiology*; D001696:Biomechanical Phenomena; D005260:Female; D005528:Foot / Q000502:physiology*; D005684:Gait / Q000502:physiology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D011312:Pressure; D012016:Reference Values; D016138:Walking
keywords: Elderly; gait feature; plantar pressure; wireless monitoring