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A Review of Gait Behavior Recognition Methods Based on Wearable Devices

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Geo-informatics in Sustainable Ecosystem and Society (GSES 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 980))

Abstract

As a new biometric recognition technique, gait behavior recognition is mainly based on the individual behavior analysis of human walking. Among them, the recognition of gait classification is a key step and an important task in the process of gait behavior recognition. Firstly, this paper analyzes the factors of data noise, and summarizes the methods of data preprocessing. Secondly, it analyzes and discusses the classification of gait features. Then it compares the algorithms of gait behavior classification and recognition; The gait classification recognition method based on Hidden Markov is reviewed, which has certain theoretical guiding significance and application value.

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Acknowledgments

This paper is found by Science and Technology Research and Development Plan Project of Handan (No. 1721203048).

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Authors and Affiliations

  1. School of Information and Electric Engineering, Hebei University of Engineering, Handan, 056038, Hebei, China

    Chang Liu, Jijun Zhao & Zhongcheng Wei

Authors
  1. Chang Liu
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  2. Jijun Zhao
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  3. Zhongcheng Wei
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Corresponding author

Correspondence to Chang Liu .

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Editors and Affiliations

  1. Eastern Michigan University, Ypsilanti, MI, USA

    Yichun Xie

  2. Hebei University of Engineering, Handan, China

    Anbing Zhang

  3. Hebei University of Engineering, Handan, Hebei, China

    Haixin Liu

  4. Hebei University of Engineering, Handan, China

    Lili Feng

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Liu, C., Zhao, J., Wei, Z. (2019). A Review of Gait Behavior Recognition Methods Based on Wearable Devices. In: Xie, Y., Zhang, A., Liu, H., Feng, L. (eds) Geo-informatics in Sustainable Ecosystem and Society. GSES 2018. Communications in Computer and Information Science, vol 980. Springer, Singapore. https://doi.org/10.1007/978-981-13-7025-0_14

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  • DOI: https://doi.org/10.1007/978-981-13-7025-0_14

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-7024-3

  • Online ISBN: 978-981-13-7025-0

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