Literature DB >> 23774124

Does the evaluation of gait quality during daily life provide insight into fall risk? A novel approach using 3-day accelerometer recordings.

Aner Weiss1, Marina Brozgol, Moran Dorfman, Talia Herman, Shirley Shema, Nir Giladi, Jeffrey M Hausdorff.   

Abstract

BACKGROUND: Many approaches are used to evaluate fall risk. While their properties and performance vary, most reflect performance at a specific moment or are based on subjective self-report.
OBJECTIVE: To quantify fall risk in the home setting using an accelerometer.
METHODS: Seventy-one community-living older adults were studied. In the laboratory, fall risk was assessed using performance-based tests of mobility (eg, Timed Up and Go) and usual walking abilities were quantified. Subsequently, subjects wore a triaxial accelerometer on their lower back for 3 consecutive days. Acceleration-derived measures were extracted from segments that reflected ambulation. These included total activity duration, number of steps taken, and the amplitude and width at the dominant frequency in the power spectral density, that is, parameters reflecting step-to-step variability. Afterwards, self-report of falls was collected for 6 months to explore the predictive value.
RESULTS: Based on a history of 2 or more falls, subjects were classified as fallers or nonfallers. The number of steps during the 3 days was similar (P = .42) in the fallers (7842.1 ± 6135.6) and nonfallers (9055.3 ± 6444.7). Compared with the nonfallers, step-to-step consistency was lower in the fallers in the vertical axis (amplitude fallers, 0.58 ± 0.22 psd; nonfallers, 0.71 ± 0.18 psd; P = .008); in the mediolateral axis, step-to-step consistency was higher in the fallers (P = .014). The 3-day measures improved the identification of past and future falls status (P < .005), compared to performance-based tests.
CONCLUSIONS: Accelerometer-derived measures based on 3-day recordings are useful for evaluating fall risk as older adults perform daily living activities in their everyday home environment.

Entities:  

Keywords:  accelerometer; activities of daily living; activity monitoring; aging; fall risk; gait; mHealth

Mesh:

Year:  2013        PMID: 23774124     DOI: 10.1177/1545968313491004

Source DB:  PubMed          Journal:  Neurorehabil Neural Repair        ISSN: 1545-9683            Impact factor:   3.919


  84 in total

Review 1.  Classification of gait disturbances: distinguishing between continuous and episodic changes.

Authors:  Nir Giladi; Fay B Horak; Jeffrey M Hausdorff
Journal:  Mov Disord       Date:  2013-09-15       Impact factor: 10.338

2.  PPNa-DBS for gait and balance disorders in Parkinson's disease: a double-blind, randomised study.

Authors:  Marie-Laure Welter; Adele Demain; Claire Ewenczyk; Virginie Czernecki; Brian Lau; Amine El Helou; Hayat Belaid; Jérôme Yelnik; Chantal François; Eric Bardinet; Carine Karachi; David Grabli
Journal:  J Neurol       Date:  2015-04-23       Impact factor: 4.849

3.  Continuous Monitoring of Turning Mobility and Its Association to Falls and Cognitive Function: A Pilot Study.

Authors:  Martina Mancini; Heather Schlueter; Mahmoud El-Gohary; Nora Mattek; Colette Duncan; Jeffrey Kaye; Fay B Horak
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2016-02-25       Impact factor: 6.053

4.  Role of body-worn movement monitor technology for balance and gait rehabilitation.

Authors:  Fay Horak; Laurie King; Martina Mancini
Journal:  Phys Ther       Date:  2014-12-11

Review 5.  Clinical and methodological challenges for assessing freezing of gait: Future perspectives.

Authors:  Martina Mancini; Bastiaan R Bloem; Fay B Horak; Simon J G Lewis; Alice Nieuwboer; Jorik Nonnekes
Journal:  Mov Disord       Date:  2019-05-02       Impact factor: 10.338

6.  New evidence for gait abnormalities among Parkinson's disease patients who suffer from freezing of gait: insights using a body-fixed sensor worn for 3 days.

Authors:  Aner Weiss; Talia Herman; Nir Giladi; Jeffrey M Hausdorff
Journal:  J Neural Transm (Vienna)       Date:  2014-07-29       Impact factor: 3.575

7.  Motor Performance and Physical Activity as Predictors of Prospective Falls in Community-Dwelling Older Adults by Frailty Level: Application of Wearable Technology.

Authors:  M Jane Mohler; Christopher S Wendel; Ruth E Taylor-Piliae; Nima Toosizadeh; Bijan Najafi
Journal:  Gerontology       Date:  2016-04-30       Impact factor: 5.140

8.  Expanding the Toolkit for Studies of Aging.

Authors:  A S Buchman; P A Boyle; D A Bennett
Journal:  J Prev Alzheimers Dis       Date:  2017-04-25

9.  Analysis of Free-Living Gait in Older Adults With and Without Parkinson's Disease and With and Without a History of Falls: Identifying Generic and Disease-Specific Characteristics.

Authors:  Silvia Del Din; Brook Galna; Alan Godfrey; Esther M J Bekkers; Elisa Pelosin; Freek Nieuwhof; Anat Mirelman; Jeffrey M Hausdorff; Lynn Rochester
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2019-03-14       Impact factor: 6.053

10.  Prediction of sustained harmonic walking in the free-living environment using raw accelerometry data.

Authors:  Jacek K Urbanek; Vadim Zipunnikov; Tamara Harris; William Fadel; Nancy Glynn; Annemarie Koster; Paolo Caserotti; Ciprian Crainiceanu; Jaroslaw Harezlak
Journal:  Physiol Meas       Date:  2018-02-28       Impact factor: 2.833

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