Estimate of gait speed by using persons' walk ratio or step-frequency in older adults.
Activity monitoring
Gait speed
Older adults
Step-frequency
Walk ratio
Journal
Aging clinical and experimental research
ISSN: 1720-8319
Titre abrégé: Aging Clin Exp Res
Pays: Germany
ID NLM: 101132995
Informations de publication
Date de publication:
Nov 2021
Nov 2021
Historique:
received:
24
02
2021
accepted:
09
03
2021
pubmed:
30
3
2021
medline:
19
11
2021
entrez:
29
3
2021
Statut:
ppublish
Résumé
Gait speed estimation using wearable inertial sensors during daily activities suffers from high complexity and inaccuracies in distance estimation when integrating acceleration signals. The aim of the study was to investigate the agreement between the methods of gait speed estimation using the persons' walk ratio (step-length/step-frequency relation) or step-frequency (number of steps per minute) and a "gold standard". For this cross-sectional validation study, 20 healthy community-dwelling older persons (mean age 72.1 years; 70% women) walked at slow, normal, and fast speed over an instrumented walkway (reference measure). Gait speed was calculated using the person's pre-assessed walk ratio. Furthermore, the duration of walking and number of steps were used for calculation. The agreement between gait speed calculation using the walk ratio or step-frequency (adjusted to body height) and reference was r = 0.98 and r = 0.93, respectively. Absolute and relative mean errors of calculated gait speed using pre-assessed walk ratio ranged between 0.03-0.07 m/s and 1.97-4.17%, respectively. After confirmation in larger cohorts of healthy community-dwelling older adults, the mean gait speed of single walking bouts during activity monitoring can be estimated using the person's pre-assessed walk ratio. Furthermore, the mean gait speed can be calculated using the step-frequency and body height and can be an additional parameter in stand-alone activity monitoring.
Sections du résumé
BACKGROUND AND AIMS
OBJECTIVE
Gait speed estimation using wearable inertial sensors during daily activities suffers from high complexity and inaccuracies in distance estimation when integrating acceleration signals. The aim of the study was to investigate the agreement between the methods of gait speed estimation using the persons' walk ratio (step-length/step-frequency relation) or step-frequency (number of steps per minute) and a "gold standard".
METHODS
METHODS
For this cross-sectional validation study, 20 healthy community-dwelling older persons (mean age 72.1 years; 70% women) walked at slow, normal, and fast speed over an instrumented walkway (reference measure). Gait speed was calculated using the person's pre-assessed walk ratio. Furthermore, the duration of walking and number of steps were used for calculation.
RESULTS
RESULTS
The agreement between gait speed calculation using the walk ratio or step-frequency (adjusted to body height) and reference was r = 0.98 and r = 0.93, respectively. Absolute and relative mean errors of calculated gait speed using pre-assessed walk ratio ranged between 0.03-0.07 m/s and 1.97-4.17%, respectively.
DISCUSSION AND CONCLUSIONS
CONCLUSIONS
After confirmation in larger cohorts of healthy community-dwelling older adults, the mean gait speed of single walking bouts during activity monitoring can be estimated using the person's pre-assessed walk ratio. Furthermore, the mean gait speed can be calculated using the step-frequency and body height and can be an additional parameter in stand-alone activity monitoring.
Identifiants
pubmed: 33778931
doi: 10.1007/s40520-021-01832-z
pii: 10.1007/s40520-021-01832-z
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2989-2994Informations de copyright
© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.
Références
Quach L, Galica AM, Jones RN et al (2011) The nonlinear relationship between gait speed and falls: the maintenance of balance, independent living, intellect, and zest in the elderly of Boston Study. J Am Geriatr Soc 59:1069–1073
doi: 10.1111/j.1532-5415.2011.03408.x
Schoon Y, Bongers K, Van Kempen J, Melis R, Olde Rikkert M (2014) Gait speed as a test for monitoring frailty in community-dwelling older people has the highest diagnostic value compared to step length and chair rise time. Eur J Phys Rehabil Med 50:693–701
pubmed: 25077426
Cesari M, Kritchevsky SB, Penninx BWJH et al (2005) Prognostic value of usual gait speed in well-functioning older people–results from the health, aging and body composition study. J Am Geriatr Soc 53:1675–1680
doi: 10.1111/j.1532-5415.2005.53501.x
Studenski S, Perera S, Patel K et al (2011) Gait speed and survival in older adults. JAMA 305:50–58
doi: 10.1001/jama.2010.1923
Fritz S, Lusardi M (2009) White paper: “walking speed: the sixth vital sign”. J Geriatr Phys Ther 32:46–49
doi: 10.1519/00139143-200932020-00002
Foucher KC, Thorp LE, Orozco D, Hildebrand M, Wimmer MA (2010) Differences in preferred walking speeds in a gait laboratory compared with the real world after total hip replacement. Arch Phys Med Rehabil 91:1390–1395
doi: 10.1016/j.apmr.2010.06.015
Stellmann JP, Neuhaus A, Götze N et al (2015) Ecological validity of walking capacity tests in multiple sclerosis. PLoS One 10:e0123822
doi: 10.1371/journal.pone.0123822
Moe-Nilssen R, Helbostad JL (2004) Estimation of gait cycle characteristics by trunk accelerometry. J Biomech 37:121–126
doi: 10.1016/S0021-9290(03)00233-1
Zijlstra W (2004) Assessment of spatio-temporal parameters during unconstrained walking. Eur J Appl Physiol 92:39–44
doi: 10.1007/s00421-004-1041-5
Tudor-Locke C, Aguiar EJ, Han H et al (2019) Walking cadence (steps/min) and intensity in 21–40 year olds: CADENCE-adults. Int J Behav Nutr Phys Act 16:8
doi: 10.1186/s12966-019-0769-6
Brown JC, Harhay MO, Harhay MN (2014) Walking cadence and mortality among community-dwelling older adults. J Gen Intern Med 29:1263–1269
doi: 10.1007/s11606-014-2926-6
Granat M, Clarke C, Holdsworth R, Stansfield B, Dall P (2015) Quantifying the cadence of free-living walking using event-based analysis. Gait Posture 42:85–90
doi: 10.1016/j.gaitpost.2015.04.012
Schimpl M, Lederer C, Daumer M (2011) Development and validation of a new method to measure walking speed in free-living environments using the actibelt® platform. PLoS ONE 6:e23080
doi: 10.1371/journal.pone.0023080
Bogen B, Moe-Nilssen R, Ranhoff AH, Aaslund KM (2018) The walk ratio: investigation of invariance across walking conditions and gender in community-dwelling older people. Gait Posture 61:479–482
doi: 10.1016/j.gaitpost.2018.02.019
Egerton T, Danoudis M, Huxham F, Iansek R (2011) Central gait control mechanisms and the stride length—cadence relationship. Gait Posture 34:178–182
doi: 10.1016/j.gaitpost.2011.04.006
Paraschiv-Ionescu A, Buchser EE, Rutschmann B, Najafi B, Aminian K (2004) Ambulatory system for the quantitative and qualitative analysis of gait and posture in chronic pain patients treated with spinal cord stimulation. Gait Posture 20:113–125
doi: 10.1016/j.gaitpost.2003.07.005
Taraldsen K, Askim T, Sletvold O et al (2011) Evaluation of a body-worn sensor system to measure physical activity in older people with impaired function. PhysTher 91:277–285
Thabane L, Ma J, Chu R et al (2010) A tutorial on pilot studies: the what, why and how. BMC Med Res Methodol 10:1
doi: 10.1186/1471-2288-10-1
Cutlip RG, Mancinelli C, Huber F, DiPasquale J (2000) Evaluation of an instrumented walkway for measurement of the kinematic parameters of gait. Gait Posture 12:134–138
doi: 10.1016/S0966-6362(00)00062-X
Lindemann U, Najafi B, Zijlstra W et al (2008) Distance to achieve steady state walking speed in frail elderly persons. Gait Posture 27:91–96
doi: 10.1016/j.gaitpost.2007.02.005
Charlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40:373–383
doi: 10.1016/0021-9681(87)90171-8
Lindemann U (2020) Spatiotemporal gait analysis of older persons in clinical practice and research: which parameters are relevant? Z Gerontol Geriatr 53:171–178
doi: 10.1007/s00391-019-01520-8
Aboutorabi A, Arazpour M, Bahramizadeh M, Hutchins SW, Fadayevatan R (2016) The effect of aging on gait parameters in able-bodied older subjects: a literature review. Aging Clin Exp Res 28:393–405
doi: 10.1007/s40520-015-0420-6
Bohannon RW (1997) Comfortable and maximum walking speed of adults aged 20–79 years: reference values and determinants. Age Ageing 26:15–19
doi: 10.1093/ageing/26.1.15
Hollman JH, McDade EM, Petersen RC (2014) Normative spatiotemporal gait parameters in older adults. Gait Posture 34:111–118
doi: 10.1016/j.gaitpost.2011.03.024
Thingstad P, Egerton T, Ihlen EF, Taraldsen K, Moe-Nilssen R, Helbostad JL (2015) Identification of gait domains and key gait variables following hip fracture. BMC Geriatr 15:150
doi: 10.1186/s12877-015-0147-4
Van Schooten KS, Pijnappels M, Rispens SM et al (2016) Daily-life gait quality as predictor of falls in older people: a 1-year prospective cohort study. PLoS ONE 11:e0158623
doi: 10.1371/journal.pone.0158623
Moe-Nilssen R, Helbostad JL (2020) Spatiotemporal gait parameters for older adults—an interactive model adjusting reference data for age, gender, and body height. Gait Posture 82:220–226
doi: 10.1016/j.gaitpost.2020.09.009
Bruening DA, Frimenko RE, Goodyear CD, Bowden DR, Fullenkamp AM (2015) Sex differences in whole body gait kinematics at preferred speeds. Gait Posture 41:540–545
doi: 10.1016/j.gaitpost.2014.12.011
Morris ME, Iansek R, Matyas TA, Summers JJ (1994) The pathogenesis of gait hypokinesia in Parkinson’s disease. Brain 117:1169–1181
doi: 10.1093/brain/117.5.1169
Relkin N, Marmarou A, Klinge P, Bergsneider M, Black PM (2005) Diagnosing idiopathic normal-pressure hydrocephalus. Neurosurgery 57(3 Suppl):S4-16
pubmed: 16160425