Martina Furrer1, Lukas Bichsel2, Michael Niederer3, Heiner Baur1, Stefan Schmid4. 1. Discipline of Physiotherapy, Health Division, Bern University of Applied Sciences, Bern, Switzerland. 2. Institute for Rehabilitation and Performance Technology, Department of Engineering and Information Technology, Bern University of Applied Sciences, Burgdorf, Switzerland. 3. Institute for Physiotherapy, School of Health Professions, Zurich University of Applied Sciences, Zurich, Switzerland. 4. Discipline of Physiotherapy, Health Division, Bern University of Applied Sciences, Bern, Switzerland. Electronic address: stefanschmid79@gmail.com.
Abstract
INTRODUCTION: 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. CONCLUSION: 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.
INTRODUCTION: 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. CONCLUSION: 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: Dylan Kobsar; Jesse M Charlton; Calvin T F Tse; Jean-Francois Esculier; Angelo Graffos; Natasha M Krowchuk; Daniel Thatcher; Michael A Hunt Journal: J Neuroeng Rehabil Date: 2020-05-11 Impact factor: 4.262