@article{ref1,
title="A validated smartphone-based assessment of gait and gait variability in Parkinson's disease",
journal="PLoS one",
year="2015",
author="Ellis, Robert J. and Ng, Yee Sien and Zhu, Shenggao and Tan, Dawn M. and Anderson, Boyd and Schlaug, Gottfried and Wang, Ye",
volume="10",
number="10",
pages="e0141694-e0141694",
abstract="BACKGROUND: A well-established connection exists between increased gait variability and greater fall likelihood in Parkinson's disease (PD); however, a portable, validated means of quantifying gait variability (and testing the efficacy of any intervention) remains lacking. Furthermore, although rhythmic auditory cueing continues to receive attention as a promising gait therapy for PD, its widespread delivery remains bottlenecked. The present paper describes a smartphone-based mobile application (&quot;SmartMOVE&quot;) to address both needs. <br><br>METHODS: The accuracy of smartphone-based gait analysis (utilizing the smartphone's built-in tri-axial accelerometer and gyroscope to calculate successive step times and step lengths) was validated against two heel contact-based measurement devices: heel-mounted footswitch sensors (to capture step times) and an instrumented pressure sensor mat (to capture step lengths). 12 PD patients and 12 age-matched healthy controls walked along a 26-m path during self-paced and metronome-cued conditions, with all three devices recording simultaneously. <br><br>RESULTS: Four outcome measures of gait and gait variability were calculated. Mixed-factorial analysis of variance revealed several instances in which between-group differences (e.g., increased gait variability in PD patients relative to healthy controls) yielded medium-to-large effect sizes (eta-squared values), and cueing-mediated changes (e.g., decreased gait variability when PD patients walked with auditory cues) yielded small-to-medium effect sizes-while at the same time, device-related measurement error yielded small-to-negligible effect sizes. <br><br>CONCLUSION: These findings highlight specific opportunities for smartphone-based gait analysis to serve as an alternative to conventional gait analysis methods (e.g., footswitch systems or sensor-embedded walkways), particularly when those methods are cost-prohibitive, cumbersome, or inconvenient.<p /> <p>Language: en</p>",
language="en",
issn="1932-6203",
doi="10.1371/journal.pone.0141694",
url="http://dx.doi.org/10.1371/journal.pone.0141694"
}