A Validated Smartphone-Based Assessment of Gait and Gait Variability in Parkinson's Disease

被引:78
作者
Ellis, Robert J. [1 ]
Ng, Yee Sien [3 ]
Zhu, Shenggao [2 ]
Tan, Dawn M. [3 ]
Anderson, Boyd [1 ]
Schlaug, Gottfried [4 ,5 ]
Wang, Ye [1 ,2 ]
机构
[1] Natl Univ Singapore, Sch Comp, Singapore 117417, Singapore
[2] NUS Grad Sch Integrat Sci & Engn, Singapore 117456, Singapore
[3] Singapore Gen Hosp, Dept Rehabil Med, Singapore 117456, Singapore
[4] Beth Israel Deaconess Med Ctr, Dept Neurol, Boston, MA 02215 USA
[5] Harvard Univ, Sch Med, Boston, MA 02215 USA
来源
PLOS ONE | 2015年 / 10卷 / 10期
基金
新加坡国家研究基金会;
关键词
RHYTHMIC AUDITORY-STIMULATION; OLDER-ADULTS; EFFECT SIZE; SPATIOTEMPORAL PARAMETERS; MOVEMENT-DISORDERS; WEARABLE SENSORS; FALLS; WALKING; PEOPLE; MOTOR;
D O I
10.1371/journal.pone.0141694
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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 smart-phone-based mobile application ("SmartMOVE") to address both needs. 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. 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. 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.
引用
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页数:22
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