Low-cost piezoelectric footswitch system for measuring temporal parameters during walking

  • Authors

    • Gustavo Balbinot Department of Neuroscience, Federal University of Rio Grande do Norte (UFRN), Natal, RN, Brazil Brain Institute
    • Clarissa Pedrini Schuch Biomechanics Lab., Brazilian Institute for Shoes, Leather and Parts (IBTeC), Novo Hamburgo, RS, Brazil.
    • Milton Antonio Zaro Biomechanics Lab., Brazilian Institute for Shoes, Leather and Parts (IBTeC), Novo Hamburgo, RS, Brazil.l
    • Marco Aurélio Vaz School of Physical Education, Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
    2014-02-18
    https://doi.org/10.14419/ijet.v3i1.1733

  • Human walking is one of the most investigated biomechanical events, and gait analysis depends on accurate measurement of heel strike (HS) and toe off (TO). The purpose of this study was to construct and validate a low-cost footswitch system for the measurement of temporal gait parameters. Ten young healthy subjects participated of the validation and test of the footswitch system with two different footwear, Bland-Altman analysis showed 98% and 95% of validation data within the limits of agreement, for HS and TO respectively (mean difference of 16ms±1ms and 20ms±9ms) and the temporal parameters measured during treadmill walking at a speed of 4.5km.h-1 showed results similar to those found in the literature for normal walking. The outcomes confirm low CoVs for the instrumented athletic and instability shoe, respectively: (1.52±0.61)% and (1.90±0.73)% for contact time, (2.17±0.95)% and (2.57±0.95)% for balance time, (0.84±0.28)% and (1.12±0.53)% for stride time. The low-cost footswitch system described and validated in the present study has an important practical applicability, mostly for emerging and developing countries biomechanics labs.

     

    Keywords: Footswitch System, Gait Analysis, Locomotion, Low-Cost, Walk.

  • References

    1. R. Enoka, Bases Neuromecânicas da Cinesiologia, Manole, São Paulo, Brazil, 2000.
    2. D.A. Winter, Biomechanics and motor control of human movement, John Wiley & Sons Ltda, New Jersey, USA, 2005.
    3. J.K. Lee, E.J. Park, Quasi real-time gait event detection using shank-attached gyroscopes, Med Biol Eng Comput. 49(6) (2011) 707-712.
    4. J. Perry, Gait analysis: normal and pathological function, Thorofare, New Jersey, USA, 1992.
    5. T. Andriacchi, E. Alexander, Studies of human locomotion: past, present and future, J Biomech. 33(10) (2000) 1217-1224.
    6. J. Hausdorff, Z. Ladin, J. Wei, Footswitch system for measurement of the temporal parameters of gait, J Biomech. 28(3) (1995) 347-351.
    7. J. Wall, J. Crosbieb, Accuracy and reliability of temporal gait measurement, Gait & Posture 4(4) (1996) 293-296.
    8. P. Araújo, R. Kirkwood, E. Figueiredo, Validity and intra- and inter-rater reliability of the Observational Gait Scale for children with spastic cerebral palsy, Rev Bras Fisioter. 13(3) (2009) 267-273.
    9. J. Brinkmann, J. Perry, Rate and range of knee motion during ambulation in healthy and arthritic subjects, Phys Therapy. 65(7) (1985) 1055-1060.
    10. C. Powers, L. Boyd, L. Torburn, J. Perry, Stair ambulation in persons with transtibial amputation: analysis the Seattle LightFoot, J Rehab Res Development. 34(1) (1997) 9-18.
    11. A. Mansfield, G. Lyons, The use of accelerometry to detect heel contact events for use as a sensor in FES assisted walking, Med Eng & Physics. 25 (2003) 879–885.
    12. T. Kesar, R. Perumal, D. Reisman, et al., Functional electrical stimulation of ankle plantarflexor and dorsiflexor muscles, Stroke 40(12) (2009) 3821-3827.
    13. M. Hanlon, R. Anderson, Real-time gait event detection using wearable sensors, Gait & Posture 30(4) (2009) 523–527.
    14. B. Auvinet, G. Berrut, C. Touzard, et al., Reference data for normal subjects obtained with an accelerometric device, Gait & Posture 16(2) (2002) 124–134.
    15. J. Lee, S. Cho, Y. Lee, H. Yang, J. Lee, Portable activity monitoring system for temporal parameters of gait cycles, J Med Syst. 34(5) (2010) 959–966.
    16. S. Bus, A. Lange, A comparison of the 1-step, 2-step, and 3-step protocols for obtaining barefoot plantar pressure data in the diabetic neuropathic foot, Clinical Biomech. 20(9) (2005) 892–899.
    17. J. Bland, D. Altman, Statistical methods for assessing agreement between two methods of clinical measurement, Lancet. 327(8476) (1986) 307-310.
    18. O. Beauchet, G. Allali, C. Annweiler, et al., Gait variability among healthy adults: low and high stride-to-stride variability are both a reflection of gait stability, Gerontology 55(6) (2009) 702–706.
    19. J. Rueterbories, E. Spaich, B. Larsen, O. Andersen, Methods for gait event detection and analysis in ambulatory systems, Med Eng Phys. 32(6) (2010) 545-552.

  • Downloads

    Additional Files

  • How to Cite

    Balbinot, G., Schuch, C. P., Zaro, M. A., & Vaz, M. A. (2014). Low-cost piezoelectric footswitch system for measuring temporal parameters during walking. International Journal of Engineering & Technology, 3(1), 75-81. https://doi.org/10.14419/ijet.v3i1.1733