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Boer, N. de, Abdi, H., Fielding, M., & Nahavandi, S. (2017). Segmentation and Feature Extraction of Human Gait Motion. KnE Engineering, 2(1), 267-273. https://doi.org/10.18502/keg.v2i2.625

https://doi.org/10.18502/keg.v2i2.625

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authors

  • Nicholas de Boer
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  • Hamid Abdi
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  • Michael Fielding
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  • Saeid Nahavandi
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Published Date

  • Feb 9, 2017

Segmentation and Feature Extraction of Human Gait Motion

KnE Engineering / The International Conference on Design and Technology / Pages 267-273

Abstract

This paper presents segmentation and feature extraction of human gait motion. The methodology of this paper focuses on segmenting ‘XYZ’ position curves, in reference to time of gait motion based on the velocity or acceleration of the movement. The extracted features include amplitude, time, and equally spaced sample data, maximum and minimum for each segment. The results can be used for reconstruction of a viable dataset that is critical for simulation and validation of human gaits. We propose a method to enables the fitting of the same curve with limited data. Such data sets may prove valuable for studying impairments and improving simulations of rehabilitation tools, and statistical classification for researchers worldwide.

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