Literature DB >> 24831570

Are the spatio-temporal parameters of gait capable of distinguishing a faller from a non-faller elderly?

N Mortaza1, N A Abu Osman, N Mehdikhani.   

Abstract

Fall is a common and a major cause of injuries. It is important to find elderlies who are prone to falls. The majority of serious falls occur during walking among the older adults. Analyzing the spatio-temporal parameters of walking is an easy way of assessment in the clinical setting, but is it capable of distinguishing a faller from a non-faller elderly? Through a systematic review of the literature, the objective of this systematic review was to identify and summarize the differences in the spatio-temporal parameters of walking in elderly fallers and non-fallers and to find out if these parameters are capable of distinguishing a faller from a non-faller. All original research articles which compared any special or temporal walking parameters in faller and non-faller elderlies were systematically searched within the Scopus and Embase databases. Effect size analysis was also done to standardize findings and compare the gait parameters of fallers and non-fallers across the selected studies. The electronic search led to 5381 articles. After title and abstract screening 30 articles were chosen; further assessment of the full texts led to 17 eligible articles for inclusion in the review. It seems that temporal measurements are more sensitive to the detection of risk of fall in elderly people. The results of the 17 selected studies showed that fallers have a tendency toward a slower walking speed and cadence, longer stride time, and double support duration. Also, fallers showed shorter stride and step length, wider step width and more variability in spatio-temporal parameters of gait. According to the effect size analysis, step length, gait speed, stride length and stance time variability were respectively more capable of differentiating faller from non-faller elderlies. However, because of the difference of methodology and number of studies which investigated each parameter, these results are prone to imprecision. Spatio-temporal analysis of level walking is not sufficient and cannot act as a reliable predictor of falls in elderly individuals.

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Year:  2014        PMID: 24831570

Source DB:  PubMed          Journal:  Eur J Phys Rehabil Med        ISSN: 1973-9087            Impact factor:   2.874


  37 in total

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Journal:  J Gerontol A Biol Sci Med Sci       Date:  2016-02-25       Impact factor: 6.053

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

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Journal:  Phys Ther       Date:  2014-12-11

3.  Standing Balance and Spatiotemporal Aspects of Gait Are Impaired Upon Nocturnal Awakening in Healthy Late Middle-Aged and Older Adults.

Authors:  Amanda L McBean; Raymond P Najjar; Ronald A Schuchard; Courtney D Hall; Cheng-Ann Wang; Ban Ku; Jamie M Zeitzer
Journal:  J Clin Sleep Med       Date:  2016-11-15       Impact factor: 4.062

4.  An investigation of the spatio-temporal parameters of gait and margins of stability throughout adulthood.

Authors:  Nolan Herssens; Tamaya van Criekinge; Wim Saeys; Steven Truijen; Luc Vereeck; Vincent van Rompaey; Ann Hallemans
Journal:  J R Soc Interface       Date:  2020-05-20       Impact factor: 4.118

5.  Gait characteristics associated with walking speed decline in older adults: results from the Baltimore Longitudinal Study of Aging.

Authors:  Gerald J Jerome; Seung-uk Ko; Danielle Kauffman; Stephanie A Studenski; Luigi Ferrucci; Eleanor M Simonsick
Journal:  Arch Gerontol Geriatr       Date:  2015-01-13       Impact factor: 3.250

6.  Age and Cognitive Stress Influences Motor Skill Acquisition, Consolidation, and Dual-Task Effect in Humans.

Authors:  Keith R Cole; Richard K Shields
Journal:  J Mot Behav       Date:  2019-01-02       Impact factor: 1.328

7.  Differential Gait Patterns by History of Falls and Knee Pain Status in Healthy Older Adults: Results From the Baltimore Longitudinal Study of Aging.

Authors:  Seung-Uk Ko; Gerald J Jerome; Eleanor M Simonsick; Stephanie Studenski; Luigi Ferrucci
Journal:  J Aging Phys Act       Date:  2018-08-27       Impact factor: 1.961

8.  Wearables and Deep Learning Classify Fall Risk From Gait in Multiple Sclerosis.

Authors:  Brett M Meyer; Lindsey J Tulipani; Reed D Gurchiek; Dakota A Allen; Lukas Adamowicz; Dale Larie; Andrew J Solomon; Nick Cheney; Ryan S McGinnis
Journal:  IEEE J Biomed Health Inform       Date:  2021-05-11       Impact factor: 5.772

Review 9.  Perceptual-motor styles.

Authors:  Pierre-Paul Vidal; Francesco Lacquaniti
Journal:  Exp Brain Res       Date:  2021-03-06       Impact factor: 2.064

10.  Walking Gait Before and After Chiropractic Care Following Fifth Metatarsal Fractures: A Single Case Kinetic and Kinematic Study.

Authors:  Brent S Russell; Kathryn T Hoiriis; Ronald S Hosek
Journal:  J Chiropr Med       Date:  2018-06-14
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