title: Multiple gait parameters derived from iPod accelerometry predict age-related gait changes.
abstract: Normative data of how natural aging affects gait can serve as a frame of reference for changes in gait dynamics due to pathologies. Therefore, the present study aims (1) to identify gait variables sensitive to age-related changes in gait over the adult life span using the iPod and (2) to assess if these variables accurately distinguish young (aged 18-45) from healthy older (aged 46-75) adults.
  
  
  
  Trunk accelerations were recorded with an iPod Touch in 59 healthy adults during three minutes of overground walking. Gait variables included gait speed and accelerometry-based gait variables (stride, amplitude, frequency, and trajectory-related variables) in the anterior-posterior (AP) and medio-lateral (ML) directions. Multivariate partial least square analysis (PLS) identified variables sensitive to age-related differences in gait. To classify young and old adults, a PLS-discriminant analysis (PLS-DA) was used to test the accuracy of these variables.
  
  
  
  The PLS model explained 42% of variation in age. Influential variables were: mean stride time, phase variability index, root mean square, stride variability, AP sample entropy and ML maximal Lyaponov exponent. PLS-DA classified 83% of the participants correctly with a sensitivity of 83% and specificity of 71%.
  
  
  
  Contrary to the frequently reported high gait variability observed in old adults with frailty and fall history, the present study showed that younger compared with older healthy adults had a more variable, less predictable and more symmetrical gait pattern. A model based on a combination of variables reflecting gait dynamics, could distinguish healthy younger adults from older adults.
authors.affiliation: University of Groningen, University Medical Center Groningen, Center for Human Movement Sciences, The Netherlands; Univ. Grenoble-Alpes, AGIM, La Tronche, France. Electronic address: n.m.kosse@gmail.com.
authors.forename: Nienke M
authors.initials: NM
authors.lastname: Kosse
authors.affiliation: Univ. Grenoble-Alpes, AGIM, La Tronche, France; Institut Universitaire de France, Paris, France.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Vuillerme
authors.affiliation: University of Groningen, University Medical Center Groningen, Center for Human Movement Sciences, The Netherlands.
authors.forename: Tibor
authors.initials: T
authors.lastname: Hortobágyi
authors.affiliation: University of Groningen, University Medical Center Groningen, Center for Human Movement Sciences, The Netherlands.
authors.forename: Claudine Jc
authors.initials: CJ
authors.lastname: Lamoth
mesh_terms: D061725:Accelerometry / Q000295:instrumentation*; D000293:Adolescent; D000328:Adult; D000368:Aged; D000375:Aging / Q000502:physiology*; D005260:Female; D005684:Gait / Q000502:physiology*; D006801:Humans; D055539:MP3-Player; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D016138:Walking; D055815:Young Adult
keywords: Accelerometer; Aging; Partial least square analysis; Walking; iPod