論文

査読有り
2015年6月

Accelerometry-Based Gait Characteristics Evaluated Using a Smartphone and Their Association with Fall Risk in People with Chronic Stroke

JOURNAL OF STROKE & CEREBROVASCULAR DISEASES
  • Takuya Isho
  • ,
  • Hideyuki Tashiro
  • ,
  • Shigeru Usuda

24
6
開始ページ
1305
終了ページ
1311
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1016/j.jstrokecerebrovasdis.2015.02.004
出版者・発行元
ELSEVIER SCIENCE BV

Background: The smartphone, which contains inertial sensors, is currently available and affordable device and has the potential to provide a self-assessment tool for health management. The aims of this study were to use a smartphone to record trunk acceleration during walking and to compare accelerometry variables between post-stroke subjects with and without a history of falling. Methods: This cross-sectional study was conducted in 2 day care centers for elderly adults. Twenty-four community-dwelling adults with chronic stroke (mean age, 71.6 +/- 9.7 years; mean time since stroke, 68.5 +/- 38.7 months) were enrolled. Acceleration of the trunk during walking was recorded in the anteroposterior and mediolateral directions and quantified using the autocorrelation coefficient, harmonic ratio, and interstride variability (coefficient of variation of root mean square acceleration). Fall history in the past 12 months was obtained by self-report. Results: Eleven participants (45.8%) reported at least one fall in the past 12 months and were classified as fallers. Fallers exhibited significantly higher interstride variability of mediolateral trunk acceleration than nonfallers. In the logistic regression analysis, interstride variability of mediolateral trunk acceleration was significantly associated with fall history (adjusted odds ratio, 1.462; 95% confidence interval, 1.009-2.120). The area under the receiver operating characteristic curve for interstride variability of mediolateral trunk acceleration to discriminate fallers from nonfallers was .745 (95% confidence interval, .527-.963). Conclusions: The results suggest that quantitative gait assessment using a smartphone can provide detailed and objective information about subtle changes in the gait pattern of stroke subjects at risk of falling.


リンク情報
DOI
https://doi.org/10.1016/j.jstrokecerebrovasdis.2015.02.004
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000355338200040&DestApp=WOS_CPL
ID情報
  • DOI : 10.1016/j.jstrokecerebrovasdis.2015.02.004
  • ISSN : 1052-3057
  • eISSN : 1532-8511
  • Web of Science ID : WOS:000355338200040

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