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Gaitography applied to prosthetic walking

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Abstract

During walking on an instrumented treadmill with an embedded force platform or grid of pressure sensors, center-of-pressure (COP) trajectories exhibit a characteristic butterfly-like shape, reflecting the medio-lateral and anterior–posterior weight shifts associated with alternating steps. We define “gaitography” as the analysis of such COP trajectories during walking (the “gaitograms”). It is currently unknown, however, if gaitography can be employed to characterize pathological gait, such as lateralized gait impairments. We therefore registered gaitograms for a heterogeneous sample of persons with a trans-femoral and trans-tibial amputation during treadmill walking at a self-selected comfortable speed. We found that gaitograms directly visualize between-person differences in prosthetic gait in terms of step width and the relative duration of prosthetic and non-prosthetic single-support stance phases. We further demonstrated that one should not only focus on the gaitogram’s shape but also on the time evolution along that shape, given that the COP evolves much slower in the single-support phase than in the double-support phase. Finally, commonly used temporal and spatial prosthetic gait characteristics were derived, revealing both individual and systematic differences in prosthetic and non-prosthetic step lengths, step times, swing times, and double-support durations. Because gaitograms can be rapidly collected in an unobtrusive and markerless manner over multiple gait cycles without constraining foot placement, clinical application of gaitography seems both expedient and appealing. Studies examining the repeatability of gaitograms and evaluating gaitography-based gait characteristics against a gold standard with known validity and reliability are required before gaitography can be clinically applied.

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Acknowledgments

The contribution of Melvyn Roerdink was supported by Veni Grant 451-09-024 of the Netherlands Organization for Scientific Research (NWO). The authors are grateful to Bert Coolen for implementing the software for online gait-event detection.

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Authors and Affiliations

  1. Faculty of Human Movement Sciences, MOVE Research Institute Amsterdam, VU University Amsterdam, Van der Boechorststraat 9, 1081 BT, Amsterdam, The Netherlands

    Melvyn Roerdink, Mariëlle W. van Ooijen & Peter J. Beek

  2. INAIL Centro Protesi, Budrio, Italy

    Andrea G. Cutti, Aurora Summa, Davide Monari & Davide Veronesi

  3. Amsterdam Rehabilitation Research Center, Reade, Amsterdam, The Netherlands

    Mariëlle W. van Ooijen

  4. School of Sport and Education, Brunel University, London, UK

    Peter J. Beek

Authors
  1. Melvyn Roerdink
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  2. Andrea G. Cutti
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  3. Aurora Summa
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  4. Davide Monari
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  5. Davide Veronesi
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  6. Mariëlle W. van Ooijen
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  7. Peter J. Beek
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Correspondence to Melvyn Roerdink.

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Roerdink, M., Cutti, A.G., Summa, A. et al. Gaitography applied to prosthetic walking. Med Biol Eng Comput 52, 963–969 (2014). https://doi.org/10.1007/s11517-014-1195-1

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  • DOI: https://doi.org/10.1007/s11517-014-1195-1

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