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Reliability and Validity of a Smartphone-based Assessment of Gait Parameters in Patients with Chronic Stroke
J Korean Soc Phys Med 2018;13(3):19-25
Published online August 31, 2018;  https://doi.org/10.13066/kspm.2018.13.3.19
© 2018 Journal of The Korean Society of Physical Medicine.

Jin Park, PT, MSc⋅Tae-Ho Kim, PT, PhD1†

Department of Physical Therapy, The Graduate School, Daegu University
1Department of Physical Therapy, Daegu University
Received April 24, 2018; Revised April 26, 2018; Accepted May 23, 2018.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
PURPOSE: Most gait assessment tools are expensive and require controlled laboratory environments. Tri-axial accelerometers have been used in gait analysis as an alternative to laboratory assessments. Many smartphones have added an accelerometer, making it possible to assess spatio-temporal gait parameters. This study was conducted to confirm the reliability and validity of a smartphone-based accelerometer at quantifying spatio-temporal gait parameters of stroke patients when attached to the body.
METHODS: We measured gait parameters using a smartphone accelerometer and gait parameters through the GAITRite analysis system and the reliability and validity of the smartphone-based accelerometer for quantifying spatio-temporal gait parameters for stroke patients were then evaluated. Thirty stroke patients were asked to walk at self-selected comfortable speeds over a 10 m walkway, during which time gait velocity, cadence and step length were computed from smartphone-based accelerometers and validated with a GAITRite analysis system.
RESULTS: Smartphone data was found to have excellent reliability (ICC2,1≥.98) for measuring the tested parameters, with a high correlation being observed between smartphone-based gait parameters and GAITRite analysis system-based gait parameters (r = .99, .97, .41 for gait velocity, cadence, step length, respectively).
CONCLUSION: The results suggest that specific opportunities exist for smartphone-based gait assessment as an alternative to conventional gait assessment. Moreover, smartphone-based gait assessment can provide objective information about changes in the spatio-temporal gait parameters of stroke subjects.
Keywords : Assessment, Gait, Smart phone, Stroke


August 2018, 13 (3)
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