Skip to main content
SpringerLink
Log in

Data set of healthy old people assessed for three walking conditions using accelerometric and opto-electronic methods

  • Original Article
  • Published:
Aging Clinical and Experimental Research Aims and scope Submit manuscript

Abstract

Background

Gait patterns of healthy aging are needed to allow a comparison with pathological situations. However, little data is available.

Objective

To present gait pattern of healthy older specially selected to be “healthy walkers”.

Method

Fifty-seven older people benefited from a geriatric assessment including clinical and functional evaluations to include only those without gait disorders. Gait data were simultaneously recorded using a tri-axial accelerometer placed on the waist and four 3D position markers placed on the feet at the level of the heel and the toe. Volunteers walked at comfortable self-selected speed (CW), fast self-selected speed (FW), and finally in dual task walking condition (DTW). The extracted gait parameters were: gait speed, stride length, stride frequency, regularity and symmetry, swing, stance and double support time and ratio and minimum toe clearance. Gait speed and stride length were normalized to the right leg length.

Results

Fifty-seven older people with a mean age of 69.7 ± 4.2 years old (range from 65 to 82 years) were included. Data were analyzed according to the gender and according to the age (<70 or ≥70 years old). After normalization to leg length, the main significant differences were shown for stride length and minimum toe clearance in CW, FW and in DTW that were shorter in women. The regularity in FW was significantly lower among older volunteers.

Conclusions

This work provides a data set considering 14 gait parameters obtained from 57 healthy old people strictly selected and assessed for three walking conditions and shows that GS, SL and MTC have to be related to the gender. The age-related impact on gait performances appears reduced in this cohort.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

We’re sorry, something doesn't seem to be working properly.

Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.

Fig. 1

Similar content being viewed by others

Abbreviations

CW:

Comfortable walking condition

FW:

Fast walking condition

GS:

Gait speed

DSR:

Double support ratio

DST:

Double support time

DTW:

Dual task walking condition

MTC:

Minimum toe clearance

NGS:

Normalised GS

NSL:

Normalised SL

REG:

Regularity

StR:

Stance ratio

SwR:

Swing ratio

StT:

Stance time

SwT:

Swing time

SF:

Stride frequency

SL:

Stride length

SYM:

Symmetry

References

  1. 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

    Article  PubMed  Google Scholar 

  2. Auvinet B, Berrut G, Touzard C et al (2002) Reference data for normal subjects obtained with an accelerometric device. Gait Posture 16:124–134. doi:10.1016/S0966-6362(01)00203-X

    Article  PubMed  Google Scholar 

  3. Bautmans I, Jansen B, Van Keymolen B et al (2011) Reliability and clinical correlates of 3D-accelerometry based gait analysis outcomes according to age and fall-risk. Gait Posture 33:366–372. doi:10.1016/j.gaitpost.2010.12.003

    Article  PubMed  Google Scholar 

  4. Hartmann A, Luzi S, Murer K et al (2009) Concurrent validity of a trunk tri-axial accelerometer system for gait analysis in older adults. Gait Posture 29:444–448. doi:10.1016/j.gaitpost.2008.11.003

    Article  PubMed  Google Scholar 

  5. Gillain S, Warzee E, Lekeu F et al (2009) The value of instrumental gait analysis in elderly healthy, MCI or Alzheimer’s disease subjects and a comparison with other clinical tests used in single and dual-task conditions. Ann Phys Rehab Med 52:453–474. doi:10.1016/j.rehab.2008.10.004

    Article  CAS  Google Scholar 

  6. Gillain S, Dramé M, Lekeu F et al (2015) Gait speed or gait variability, which one to use as a marker of risk to develop Alzheimer disease? A pilot study. Aging Clin Exp Res 28:249–255. doi:10.1007/s40520-015-0392-6

    Article  PubMed  Google Scholar 

  7. Hollman JH, McDade EM, Petersen RC (2011) Normative spatiotemporal gait parameters in older adults. Gait Posture 34 (1):111–118. doi:10.1016/j.gaitpost.2011.03.024

    Article  PubMed  PubMed Central  Google Scholar 

  8. Senden R, Grimm B, Heyligers IC et al (2009) Acceleration-based gait test for healthy subjects: Reliability and reference data. Gait Posture 30:192–196. doi:10.1016/j.gaitpost.2009.04.008

    Article  CAS  PubMed  Google Scholar 

  9. Senden R, Meijer K, Heyligers IC et al (2012) Importance of correcting for individual differences in the clinical diagnosis of gait disorders. Physiotherapy 98:320–324. doi:10.1016/j.physio.2011.06.002

    Article  CAS  PubMed  Google Scholar 

  10. Gorton Iii GE, Hebert DA, Gannotti ME (2009) Assessment of the kinematic variability among 12 motion analysis laboratories. Gait Posture 29:398–402. doi:10.1016/j.gaitpost.2008.10.060

    Article  Google Scholar 

  11. O’Sullivan K, O’Sullivan L, Campbell A et al (2012) Towards monitoring lumbo-pelvic posture in real-life situations: concurrent validity of a novel posture monitor and a traditional laboratory-based motion analysis system. Man Ther 17:77–83. doi:10.1016/j.math.2011.09.006

    Article  PubMed  Google Scholar 

  12. Schwartz C, Denoël V, Forthomme B et al (2015) Merging multi-camera data to reduce motion analysis instrumental errors using Kalman filters. Comput Methods Biomech Biomed Eng 18:952–960. doi:10.1080/10255842.2013.864640

    Article  Google Scholar 

  13. Deshpande N, Metter EJ, Bandinelli S et al (2009) Gait speed under varied challenges and cognitive decline in older persons: a prospective study. Age Ageing 38:509–514. doi:10.1093/ageing/afp093

    Article  PubMed  PubMed Central  Google Scholar 

  14. Fitzpatrick AL, Buchanan CK, Nahin RL et al (2007) Associations of gait speed and other measures of physical function with cognition in a healthy cohort of elderly persons. J Gerontol Ser A Biol Sci Med Sci 62:1244–1251

    Article  Google Scholar 

  15. Artaud F, Singh-Manoux A, Dugravot A et al (2015) Decline in fast gait speed as a predictor of disability in older adults. J Am Geriatr Soc 63:1129–1136. doi:10.1111/jgs.13442

    Article  PubMed  Google Scholar 

  16. Scherder E, Eggermont L, Swaab D et al (2007) Gait in ageing and associated dementias; its relationship with cognition. Neurosci Biobehav Rev 31:485–497. doi:10.1016/j.neubiorev.2006.11.007

    Article  PubMed  Google Scholar 

  17. Verghese J, Holtzer R, Lipton RB et al (2012) Mobility stress test approach to predicting frailty, disability, and mortality in high-functioning older adults. J Am Geriatr Soc 60:1901–1905. doi:10.1111/j.1532-5415.2012.04145.x

    Article  PubMed  PubMed Central  Google Scholar 

  18. Montero-Odasso M, Muir SW, Speechley M (2012) Dual-task complexity affects gait in people with mild cognitive impairment: the interplay between gait variability, dual tasking, and risk of falls. Arch Phys Med Rehabil 93:293–299. doi:10.1016/j.apmr.2011.08.026

    Article  PubMed  Google Scholar 

  19. Yogev-Seligmann G, Rotem-Galili Y, Mirelman A et al (2010) How does explicit prioritization alter walking during dual-task performance? Effects of age and sex on gait speed and variability. Phys Ther 90:177–186. doi:10.2522/ptj.20090043

    Article  PubMed  PubMed Central  Google Scholar 

  20. Boutaayamou M, Schwartz C, Stamatakis J et al (2015) Development and validation of an accelerometer-based method for quantifying gait events. Med Eng Phys 37:226–232. doi:10.1016/j.medengphy.2015.01.001

    Article  PubMed  Google Scholar 

  21. Ko S-u, Tolea MI, Hausdorff JM et al (2011) Sex-specific differences in gait patterns of healthy older adults: results from the baltimore longitudinal study of aging. J Biomech 44:1974–1979. doi:10.1016/j.jbiomech.2011.05.005

    Article  Google Scholar 

  22. Patterson KK, Nadkarni NK, Black SE et al (2012) Gait symmetry and velocity differ in their relationship to age. Gait Posture 35:590–594. doi:10.1016/j.gaitpost.2011.11.030

    Article  PubMed  PubMed Central  Google Scholar 

  23. Dadashi F, Mariani B, Rochat S et al (2014) Gait and foot clearance parameters obtained using shoe-worn inertial sensors in a large-population sample of older adults. Sens Basel Sens 14:443–457. doi:10.3390/s140100443

    Article  Google Scholar 

  24. Laufer Y (2005) Effect of age on characteristics of forward and backward gait at preferred and accelerated walking speed. J Gerontol Ser A Biol Sci Med Sci 60:627–632. doi:10.1093/gerona/60.5.627

    Article  Google Scholar 

  25. van Iersel MB, Ribbers H, Munneke M et al (2007) The effect of cognitive dual tasks on balance during walking in physically fit elderly people. Arch Phys Med Rehabil 88:187–191. doi:10.1016/j.apmr.2006.10.031

    Article  PubMed  Google Scholar 

  26. Hausdorff JM, Schweiger A, Herman T et al (2008) Dual-task decrements in gait: contributing factors among healthy older adults. J Gerontol Ser A Biol Sci Med Sci 63:1335–1343

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank the Dr. Sophie Christelbach and Ms Vinciane Wojtasik for helping with the volunteers recruitment and the Drs. Claire Geurten and Xavier Schmitz for helping with data acquisition. This study was supported by a Grant from the Belgian fund for scientific research (F.N.R.S.).

Author contribution statement

SG: concept and design of the study, data acquisition, presentation and discussion of the results, writing. MB: data extraction, statistical analysis, discussion of the results, writing. ND: statistical analysis, writing. CS: data acquisition, data extraction, discussion of the results, writing. MD: data acquisition, data extraction, discussion of the results, writing. CG: data acquisition, writing. FD: data acquisition, writing, corrections as native speaker. ES: concept and design of the study, methodological advice, writing. GG: concept and design of the study, methodological advice, writing. OB: concept and design of the study, methodological advice, writing. OB: concept and design of the study, methodological advice, writing. JLC: concept and design of the study, methodological advice, writing. JP: concept and design of the study, methodological advice, writing.

Author information

Authors and Affiliations

  1. Geriatric Department, University Hospital of Liège, C.H.U. site NDB, Route de Gaillarmont, 600, 4032, Chênée, Belgium

    S. Gillain, C. Gerontitis & J. Petermans

  2. INTELSIG Laboratory, Department of Electrical Engineering and Computer Science, University of Liège, Liege, Belgium

    M. Boutaayamou

  3. Public Health Department, University of Liège, Liege, Belgium

    N. Dardenne

  4. Laboratory of Human Motion Analysis, LAMH, University of Liège, Liege, Belgium

    C. Schwartz, O. Brüls & J.-L. Croisier

  5. Science of Motricity Department, University of Liège, Liege, Belgium

    M. Demonceau

  6. Neurology Department, University Hospital of Liège, Chênée, Belgium

    F. Depierreux, E. Salmon & G. Garraux

  7. Research Unit in Public Health, Epidemiology and Health Economics, University of Liège, Liege, Belgium

    O. Bruyère

Authors
  1. S. Gillain
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. Boutaayamou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. N. Dardenne
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. C. Schwartz
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. M. Demonceau
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. C. Gerontitis
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. F. Depierreux
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. E. Salmon
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. G. Garraux
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. O. Bruyère
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. O. Brüls
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. J.-L. Croisier
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. J. Petermans
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to S. Gillain.

Ethics declarations

Conflict of interest

All authors disclose any financial and personal relationships with other people or organization that could inappropriately influence their work.

Statement of human and animal rights

The medical ethical committee of the University hospital of Liège (CHU Liège, Belgium) approved the protocol.

Informed consent

All participants signed inform consent.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gillain, S., Boutaayamou, M., Dardenne, N. et al. Data set of healthy old people assessed for three walking conditions using accelerometric and opto-electronic methods. Aging Clin Exp Res 29, 1201–1209 (2017). https://doi.org/10.1007/s40520-017-0730-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40520-017-0730-y

Keywords

Search

Navigation