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Differentiating fallers from nonfallers using nonlinear variability analyses of data from a low-cost portable footswitch device: a feasibility study

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Purpose: Falls are one of the main causes of injuries in older adults. This study evaluated a low-cost footswitch device that was designed to measure gait variability and investigates whether there are any relationships between variability metrics and clinical balance tests for individuals with a history of previous falls. Methods: Sixteen older adults completed a history of falls questionnaire, three functional tests related to fall risk, and walked on a treadmill with the footswitch device. We extracted the stride times from the device and applied two nonlinear variability analyses: coefficient of variation and detrended fluctuation analysis. Results: The temporal variables and variability metrics from the footswitch device correlated with gold-standard measurements based on ground reaction force data. One variability metric (detrended fluctuation analysis) showed a significant relationship with the presence of past falls with a sensitivity of 43%. Conclusion: This feasibility study demonstrates the basis for using low-cost footswitch devices to predict fall risk.
Rocznik
Strony
139--145
Opis fizyczny
Bibliogr. 28 poz., rys., tab.
Twórcy
  • Department of Biomechanics and Center for Research in Human Movement Variability, University of Nebraska at Omaha, Omaha, Nebraska, United States of America
  • Rehabilitation Engineering Center, Institute for Rehabilitation Science and Engineering, Madonna Rehabilitation Hospitals, Lincoln, Nebraska, United States of America
  • Department of Biomechanics and Center for Research in Human Movement Variability, University of Nebraska at Omaha, Omaha, Nebraska, United States of America
  • Department of Biomechanics and Center for Research in Human Movement Variability, University of Nebraska at Omaha, Omaha, Nebraska, United States of America
Bibliografia
  • [1] BARAK Y., WAGENAAR R.C., HOLT K.G., Gait Characteristics of Elderly People With a History of Falls: A Dynamic Approach, Phys. Ther., 2006, 86, 1501–1510.
  • [2] BIZOVSKA L., SVOBODA Z., KUBONOVA E., VUILLERME N., HIRJAKOVA Z., JANURA M., The differences between overground and treadmill walking in nonlinear, entropy-based and frequency variables derived from accelerometers in young and older women – preliminary report, Acta Bioeng. Biomech., 2018, 20, 93–100.
  • [3] BRACH J.S., BERLIN J.E., VANSWEARINGEN J.M., NEWMAN A.B., STUDENSKI S.A., Too much or too little step width variability is associated with a fall history in older persons who walk at or near normal gait speed, J. Neuroeng. Rehabil., 2005, 2, 21.
  • [4] CHIU S.-L., CHOU L.-S., Variability in inter-joint coordination during walking of elderly adults and its association with clinical balance measures, Clin. Biomech., 2013, 28, 454–458.
  • [5] COUGHLIN R.F., DRISCOLL F.F., Operational amplifiers and linear integrated circuits, Prentice Hall, Upper Saddle River, NJ 2001.
  • [6] DIBBLE L.E., LANGE M., Predicting falls in individuals with Parkinson disease: a reconsideration of clinical balance measures, J. Neurol. Phys. Ther., 2006, 30, 60–7.
  • [7] FLORENCE C.S., BERGEN G., ATHERLY A., BURNS E., STEVENS J., DRAKE C., Medical Costs of Fatal and Nonfatal Falls in Older Adults, J. Am. Geriatr. Soc., 2018, 66, 693–698.
  • [8] HARWOOD R.H., Visual problems and falls, Age Ageing, 2001, 30, 13–18.
  • [9] HAUSDORFF J.M., MITCHELL S.L., FIRTION R., PENG C.K., CUDKOWICZ M.E., WEI J.Y., GOLDBERGER A.L., Altered fractal dynamics of gait: reduced stride-interval correlations with aging and Huntington’s disease, J. Appl. Physiol., 1997, 82, 262–269.
  • [10] HAUSDORFF J.M., Gait dynamics, fractals and falls: Finding meaning in the stride-to-stride fluctuations of human walking, Hum. Mov. Sci., 2007, 26, 555–589.
  • [11] HAUSDORFF J.M., EDELBERG H.K., MITCHELL S.L., GOLDBERGER A.L., WEI J.Y., Increased gait unsteadiness in community-dwelling elderly fallers, Arch. Phys. Med. Rehabil., 1997, 78, 278–83.
  • [12] HAUSDORFF J.M., RIOS D.A., EDELBERG H.K., Gait variability and fall risk in community-living older adults: A 1-year prospective study, Arch. Phys. Med. Rehabil., 2017, 82, 1050–1056.
  • [13] HAWLEY-HAGUE H., BOULTON E., HALL A., PFEIFFER K., TODD C., Older adults’ perceptions of technologies aimed at falls prevention, detection or monitoring: A systematic review, Int. J. Med. Inform., 2014, 83, 416–426.
  • [14] HERMAN T., GILADI N., GRUENDLINGER L., HAUSDORFF J.M., Six weeks of intensive treadmill training improves gait and quality of life in patients with Parkinson’s disease: a pilot study, Arch. Phys. Med. Rehabil., 2007, 88, 1154–1158.
  • [15] HORNBROOK M.C., STEVENS V.J., WINGFIELD D.J., HOLLIS J.F., GREENLICK M.R., ORY M.G., Preventing falls among community-dwelling older persons: results from a randomized trial, Gerontologist, 1994, 34, 16–23.
  • [16] JULIOUS S.A., Sample size of 12 per group rule of thumb for a pilot study, Pharm. Stat., 2005, 4, 287–291.
  • [17] KANG H.G., DINGWELL J.B., Separating the effects of age and walking speed on gait variability, Gait Posture, 2008, 27, 572–577.
  • [18] MAKI B.E., Gait changes in older adults: predictors of falls or indicators of fear, J. Am. Geriatr. Soc., 1997, 45, 313–320.
  • [19] MANCINI M., HORAK F.B., The relevance of clinical balance assessment tools to differentiate balance deficits, Eur. J. Phys. Rehabil. Med., 2010, 46, 239–48.
  • [20] MILLS P.M., BARRETT R.S., MORRISON S., Agreement between footswitch and ground reaction force techniques for identifying gait events: Inter-session repeatability and the effect of walking speed, Gait Posture, 2007, 26, 323–326.
  • [21] NEWSTEAD A.H., WALDEN G.J., GITTER A.J., Gait Variables Differentiating Fallers from Nonfallers, J. Geriatr. Phys. Ther., 2007, 30, 93–101.
  • [22] PATEL S., PARK H., BONATO P., CHAN L., RODGERS M., A review of wearable sensors and systems with application in rehabilitation, J. Neuroeng. Rehabil., 2012, 9, 21.
  • [23] PATERSON K., HILL K., LYTHGO N., Stride dynamics, gait variability and prospective falls risk in active community dwelling older women, Gait Posture, 2011, 33, 251–255.
  • [24] ROOS P.E., DINGWELL J.B., Influence of simulated neuromuscular noise on movement variability and fall risk in a 3D dynamic walking model, J. Biomech., 2010, 43, 2929–2935.
  • [25] STERGIOU N., HARBOURNE R.T., CAVANAUGH J.T., Optimal movement variability: A new theoretical perspective for neurologic physical therapy, J. Neurol. Phys. Ther., 2006, 30, 120–129.
  • [26] TOEBES M.J.P., HOOZEMANS M.J.M., MATHIASSEN S.E., DEKKER J., VAN DIEËN J.H., Measurement strategy and statistical power in studies assessing gait stability and variability in older adults, Aging Clin. Exp. Res., 2016, 28, 257–265.
  • [27] TRAN S.T., THOMAS S., DICESARE C., PFEIFFER M., SIL S., TING T.V., WILLIAMS S.E., MYER G.D., KASHIKAR-ZUCK S., A pilot study of biomechanical assessment before and after an integrative training program for adolescents with juvenile fibromyalgia, Pediatr. Rheumatol., 2016, 14, 43.
  • [28] VERGHESE J., HOLTZER R., LIPTON R.B., WANG C., Quantitative Gait Markers and Incident Fall Risk in Older Adults, Journals Gerontol. Ser. A Biol. Sci. Med. Sci., 2009, 64A, 896–901.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-63bb8671-068d-414a-a0fc-7008ddb2afa9
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