Skip to main content

Advertisement

SpringerLink
Log in

Portable Activity Monitoring System for Temporal Parameters of Gait Cycles

  • Original Paper
  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

Abstract

A portable and wireless activity monitoring system was developed for the estimation of temporal gait parameters. The new system was built using three-axis accelerometers to automatically detect walking steps with various walking speeds. The accuracy of walking step-peak detection algorithm was assessed by using a running machine with variable speeds. To assess the consistency of gait parameter analysis system, estimated parameters, such as heel-contact and toe-off time based on accelerometers and footswitches were compared for consecutive 20 steps from 19 individual healthy subjects. Accelerometers and footswitches had high consistency in the temporal gait parameters. The stance, swing, single-limb support, and double-limb support time of gait cycle revealed ICCs values of 0.95, 0.93, 0.86, and 0.75 on the right and 0.96, 0.86, 0.93, 0.84 on the left, respectively. And the walking step-peak detection accuracy was 99.15% (±0.007) for the proposed method compared to 87.48% (±0.033) for a pedometer. Therefore, the proposed activity monitoring system proved to be a reliable and useful tool for identification of temporal gait parameters and walking pattern classification.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Saremi, K., Marehbian, J., Yan, X., Regnaux, J. P., Elashoff, R., Bussel, B., and Dobkin, B. H., Reliability and validity of bilateral thigh and foot accelerometry measures of walking in healthy and hemiparetic subjects. Neurorehabil. Neural Repair. 20:297–305, 2006. doi:10.1177/1545968306287171.

    Article  Google Scholar 

  2. Abu-Faraj, Z. O., Harris, G. F., Abler, J. H., and Wertsch, J. J. A., Holter-type, microprocessor-based, rehabilitation instrument for acquisition and storage of plantar pressure data. J. Rehabil. Res. Dev. 34:187–194, 1997.

    Google Scholar 

  3. Zhu, H. S., Wertsch, J. J., Harris, G. F., Loftsgaarden, J. D., and Price, M. B., Foot pressure distribution during walking and shuffling. Arch. Phys. Med. Rehabil. 72:390–397, 1991.

    Google Scholar 

  4. Akay, M., Sekine, M., Tamura, T., Higashi, Y., and Fujimoto, T., Fractal dynamics of body motion in post-stroke hemiplegic patients during walking. J. Neural Eng. 1:111–116, 2004. doi:10.1088/1741-2560/1/2/006.

    Article  Google Scholar 

  5. Evans, A. L., Duncan, G., and Gilchrist, W., Recording accelerations in body movements. Med. Biol. Eng. Comput. 29:102–104, 1991. doi:10.1007/BF02446305.

    Article  Google Scholar 

  6. Aminian, K., Rezakhanlou, K., De Andres, E., Fritsch, C., Leyvraz, P. F., and Robert, P., Temporal feature estimation during walking using miniature accelerometers: an analysis of gait improvement after hip arthroplasty. Med. Biol. Eng. Comput. 37:686–691, 1999. doi:10.1007/BF02513368.

    Article  Google Scholar 

  7. Zijlstra, W., and Hof, A. L., Assessment of spatio-temporal gait parameters from trunk accelerations during human walking. Gait Posture. 18:1–10, 2003. doi:10.1016/S0966-6362(02)00190-X.

    Article  Google Scholar 

  8. Karantonis, D. M., Narayanan, M. R., Mathie, M., Lovell, N. H., and Celler, B. G., Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring. IEEE Trans. Inf. Technol. Biomed. 10(1):156–167, 2006. doi:10.1109/TITB.2005.856864.

    Article  Google Scholar 

  9. Sackley, C. M., Hill, H. J., Pound, K., and Foxall, A., The intra-rater reliability of the balance performance monitor when measuring sitting symmetry and weight-shift activity after stroke in a community setting. Clin. Rehabil. 19:746–750, 2005. doi:10.1191/0269215505cr863oa.

    Article  Google Scholar 

  10. Hausdorff, J. M., Ladin, Z., and Wei, J. Y., Footswitch system for measurement of the temporal parameters of gait. J. Biomech. 28:347–351, 1995. doi:10.1016/0021-9290(94)00074-E.

    Article  Google Scholar 

  11. Auvinet, B., Berrut, G., Touzard, C., Moutel, L., Collet, N., Chaleil, D., and Barrey, E., Reference data for normal subjects obtained with an accelerometric device. Gait Posture. 16:124–134, 2002. doi:10.1016/S0966-6362(01)00203-X.

    Article  Google Scholar 

  12. Portney, L. G., and Watkins, M. P., Foundations of clinical research: application to practice, 2nd edition. Prentice-Hall, New Jersey, 2000.

    Google Scholar 

Download references

Acknowledgments

This work was supported by the Korea Science and Engineering Foundation grant funded by the Korea government (MEST; No. R01-2008-000-21000-0).

Author information

Authors and Affiliations

  1. Department of Excercise & Cognitive Rehabilitation, National Rehabilitation Center Research Institute, Seoul, South Korea

    Jung-Ah Lee

  2. Department of Rehabilitation Therapy, Yonsei University, 234 Maeji-ri, Heungup-myon, Wonju, Kangwon-do, 220-710, South Korea

    Sang-Hyun Cho

  3. School of Biomedical Engineering, Research Institute of Biomedical Engineering, College of Biomedical & Life Science, Konkuk University, 322, Danwol-dong, Chungju, South Korea

    Young-Jae Lee & Jeong-Whan Lee

  4. School of Electronics and Information Engineering, Chongju University, 36 Naedok-dong, Sangdang, Chongju-si, Chungbuk-do, 360-764, South Korea

    Heui-Kyung Yang

Authors
  1. Jung-Ah Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sang-Hyun Cho
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Young-Jae Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Heui-Kyung Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jeong-Whan Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jeong-Whan Lee.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lee, JA., Cho, SH., Lee, YJ. et al. Portable Activity Monitoring System for Temporal Parameters of Gait Cycles. J Med Syst 34, 959–966 (2010). https://doi.org/10.1007/s10916-009-9311-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10916-009-9311-8

Keywords

Search

Navigation