Literature DB >> 32931560

Automatic Quantification of Tandem Walking Using a Wearable Device: New Insights Into Dynamic Balance and Mobility in Older Adults.

Natalie Ganz1, Eran Gazit1, Nir Giladi1,2, Robert J Dawe3,4, Anat Mirelman1,5, Aron S Buchman3,6, Jeffrey M Hausdorff7,8.   

Abstract

BACKGROUND: Wearable sensors are increasingly employed to quantify diverse aspects of mobility. We developed novel tandem walking (TW) metrics, validated these measures using data from community-dwelling older adults, and evaluated their association with mobility disability and measures of gait and postural control.
METHODS: Six hundred ninety-three community-dwelling older adults (age: 78.69 ± 7.12 years) wore a 3D accelerometer on their lower back while performing 3 tasks: TW, usual-walking, and quiet standing. Six new measures of TW were extracted from the sensor data along with the clinician's conventional assessment of TW missteps (ie, trip other loss of balance in which recovery occurred to prevent a fall) and duration. Principal component analysis transformed the 6 new TW measures into 2 summary TW composite factors. Logistic regression models evaluated whether these TW factors were independently associated with mobility disability.
RESULTS: Both TW factors were moderately related to the TW conventional measures (r < 0.454, p < .001) and were mildly correlated with usual-walking (r < 0.195, p < .001) and standing, postural control (r < 0.119, p < .001). The TW frequency composite factor (p = .008), but not TW complexity composite factor (p = .246), was independently associated with mobility disability in a model controlling for age, sex, body mass index, race, conventional measures of TW, and other measures of gait and postural control.
CONCLUSIONS: Sensor-derived TW metrics expand the characterization of gait and postural control and suggest that they reflect a relatively independent domain of mobility. Further work is needed to determine if these metrics improve risk stratification for other adverse outcomes (eg, falls and incident disability) in older adults.
© The Author(s) 2020. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  Aging; Disability; Gait; Mobility; Wearable sensors

Mesh:

Year:  2021        PMID: 32931560      PMCID: PMC7756682          DOI: 10.1093/gerona/glaa235

Source DB:  PubMed          Journal:  J Gerontol A Biol Sci Med Sci        ISSN: 1079-5006            Impact factor:   6.591


  27 in total

1.  Development of a multidimensional balance scale for use with functionally independent older adults.

Authors:  Debra J Rose; Nicole Lucchese; Lenny D Wiersma
Journal:  Arch Phys Med Rehabil       Date:  2006-11       Impact factor: 3.966

2.  Cognitive function is associated with the development of mobility impairments in community-dwelling elders.

Authors:  Aron S Buchman; Patricia A Boyle; Sue E Leurgans; Lisa L Barnes; David A Bennett
Journal:  Am J Geriatr Psychiatry       Date:  2011-06       Impact factor: 4.105

3.  The Minority Aging Research Study: ongoing efforts to obtain brain donation in African Americans without dementia.

Authors:  Lisa L Barnes; Raj C Shah; Neelum T Aggarwal; David A Bennett; Julie A Schneider
Journal:  Curr Alzheimer Res       Date:  2012-07       Impact factor: 3.498

4.  One-leg balance is an important predictor of injurious falls in older persons.

Authors:  B J Vellas; S J Wayne; L Romero; R N Baumgartner; L Z Rubenstein; P J Garry
Journal:  J Am Geriatr Soc       Date:  1997-06       Impact factor: 5.562

5.  iTUG, a sensitive and reliable measure of mobility.

Authors:  Arash Salarian; Fay B Horak; Cris Zampieri; Patricia Carlson-Kuhta; John G Nutt; Kamiar Aminian
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2010-04-12       Impact factor: 3.802

6.  Association Between Quantitative Gait and Balance Measures and Total Daily Physical Activity in Community-Dwelling Older Adults.

Authors:  Robert J Dawe; Sue E Leurgans; Jingyun Yang; Joshua M Bennett; Jeffrey M Hausdorff; Andrew S Lim; Chris Gaiteri; David A Bennett; Aron S Buchman
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2018-04-17       Impact factor: 6.053

7.  A Guttman health scale for the aged.

Authors:  I Rosow; N Breslau
Journal:  J Gerontol       Date:  1966-10

8.  Different Combinations of Mobility Metrics Derived From a Wearable Sensor Are Associated With Distinct Health Outcomes in Older Adults.

Authors:  Aron S Buchman; Robert J Dawe; Sue E Leurgans; Thomas A Curran; Timothy Truty; Lei Yu; Lisa L Barnes; Jeffrey M Hausdorff; David A Bennett
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2020-05-22       Impact factor: 6.591

9.  Unraveling the Association Between Gait and Mortality-One Step at a Time.

Authors:  Lisanne J Dommershuijsen; Berna M Isik; Sirwan K L Darweesh; Jos N van der Geest; M Kamran Ikram; M Arfan Ikram
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2020-05-22       Impact factor: 6.053

10.  ISway: a sensitive, valid and reliable measure of postural control.

Authors:  Martina Mancini; Arash Salarian; Patricia Carlson-Kuhta; Cris Zampieri; Laurie King; Lorenzo Chiari; Fay B Horak
Journal:  J Neuroeng Rehabil       Date:  2012-08-22       Impact factor: 4.262

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