title: Validation of a smartphone-based measurement tool for the quantification of level walking.
abstract: BACKGROUND
  It is important to assess and quantify gait in order to determine the severity of impairments during gait and to evaluate therapeutic interventions. However, laboratory gait assessment is expensive and time consuming and there is a lack of an easily applicable tool for the quantification of gait in clinical practice. The aim of this study was to validate a smartphone-based measurement tool for the quantification of level walking.
  
  
  METHODS
  Vertical center of mass displacement and step duration of 22 healthy young adults were assessed by a smartphone application and a motion capture system. Intra-session reliability was evaluated by repeated-measures ANOVA, intraclass correlation coefficient (ICC), and standard error of measurement. In order to evaluate the concurrent validity of the smartphone application, smartphone- and motion capture-derived values were compared by Pearson correlation coefficient and Bland-Altman limits of agreement.
  
  
  RESULTS
  Six out of eight variables derived by the smartphone application showed an excellent reliability (ICC≥0.75) and all variables correlated significantly with measurements of the motion capture system with moderate to strong correlations ranging from 0.61 to 0.92.
  
  
  CONCLUSIONS
  The results showed a great potential of the smartphone application to be a user-friendly and valid tool for the assessment of gait in clinical practice. Further research needs to investigate whether the smartphone application is able to detect differences in gait patterns following therapeutic or orthopedic interventions and whether it is valid for the quantification of gait in people with movement disorders.
authors.affiliation: Discipline of Physiotherapy, Health Division, Bern University of Applied Sciences, Bern, Switzerland.
authors.forename: Martina
authors.initials: M
authors.lastname: Furrer
authors.affiliation: Institute for Rehabilitation and Performance Technology, Department of Engineering and Information Technology, Bern University of Applied Sciences, Burgdorf, Switzerland.
authors.forename: Lukas
authors.initials: L
authors.lastname: Bichsel
authors.affiliation: Institute for Physiotherapy, School of Health Professions, Zurich University of Applied Sciences, Zurich, Switzerland.
authors.forename: Michael
authors.initials: M
authors.lastname: Niederer
authors.affiliation: Discipline of Physiotherapy, Health Division, Bern University of Applied Sciences, Bern, Switzerland.
authors.forename: Heiner
authors.initials: H
authors.lastname: Baur
authors.affiliation: Discipline of Physiotherapy, Health Division, Bern University of Applied Sciences, Bern, Switzerland. Electronic address: stefanschmid79@gmail.com.
authors.forename: Stefan
authors.initials: S
authors.lastname: Schmid
mesh_terms: D061725:Accelerometry / Q000379:methods*; D000328:Adult; D003430:Cross-Sectional Studies; D005260:Female; D005684:Gait; D064368:Healthy Volunteers; D006801:Humans; D008297:Male; D063731:Mobile Applications; D015203:Reproducibility of Results; D000068997:Smartphone; D016138:Walking; D055815:Young Adult
keywords: Gait analysis; Reliability; Trunk accelerometry; Validity