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Posture Recognition and Heading Estimation Based on Machine Learning Using MEMS Sensors

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Artificial Intelligence for Communications and Networks (AICON 2019)

Abstract

With the popularity of smartphones and the performance improvement of embedded sensor, the smartphone has become the most important terminal device in motion recognition and indoor positioning. In this paper, the methods of the smartphone posture recognition and the pedestrian heading estimation are proposed. We analyze the signal characteristic of the accelerometer and the gyroscope, the representative feature information is extracted and a classifier based on DT model is proposed. Besides, considering the different postures of the smartphone, we propose an improved heading estimation method, which utilizes a weighted-average operation and combines the principal component analysis-based (PCA-based) method and the angle deviation method innovatively. The results of the experiments show that the average accuracy of posture recognition is nearly 97.1%, which can satisfy the pattern recognition in the process of pedestrian navigation. The average error of the proposed heading estimation is 6.2° and the performance is improved than the single PCA-based and angle deviation method.

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Acknowledgments

This work was supported in part by the Fundamental Research Funds for the Central Universities under Grant HEUCF180801, and in part by the National Key Research and Development Plan of China under Grant 2016YFB0502100 and Grant 2016YFB0502103.

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Authors and Affiliations

  1. College of Information and Communication Engineering, Harbin Engineering University, Harbin, 150001, China

    Boyuan Wang & Xuelin Liu

  2. The 54th Research Institute of China Electronics Technology Group Corporation, Shijiazhuang, 050081, China

    Baoguo Yu, Ruicai Jia & Lu Huang

  3. State Key Laboratory of Satellite Navigation System and Equipment Technology, Shijiazhuang, 050081, China

    Baoguo Yu, Ruicai Jia & Lu Huang

Authors
  1. Boyuan Wang
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  2. Xuelin Liu
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  3. Baoguo Yu
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  4. Ruicai Jia
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  5. Lu Huang
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Corresponding author

Correspondence to Boyuan Wang .

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Editors and Affiliations

  1. Harbin Institute of Technology, Harbin, China

    Shuai Han

  2. Harbin Institute of Technology, Harbin, China

    Liang Ye

  3. Harbin Institute of Technology, Harbin, China

    Weixiao Meng

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Wang, B., Liu, X., Yu, B., Jia, R., Huang, L. (2019). Posture Recognition and Heading Estimation Based on Machine Learning Using MEMS Sensors. In: Han, S., Ye, L., Meng, W. (eds) Artificial Intelligence for Communications and Networks. AICON 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 287. Springer, Cham. https://doi.org/10.1007/978-3-030-22971-9_42

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  • DOI: https://doi.org/10.1007/978-3-030-22971-9_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-22970-2

  • Online ISBN: 978-3-030-22971-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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