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Automatic Sleeping Posture Detection in Ballistocardiography

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Communications, Signal Processing, and Systems (CSPS 2017)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 463))

Abstract

Sleeping posture is an important factor in the quality of sleep. In this paper, we present a study on the feasibility of the automatic detection of personal sleeping posture from ballistocardiograms (BCGs) recorded by unobtrusive loadcell-embedded mattress. The proposed system is intended as a screening and monitoring tool in home-healthcare applications and provides reference for patients with chronic disease to adjust sleeping pattern. This work extracts the features of a heartbeat waveform pattern obtained from BCG and use the Random Forest classifier to classify various sleeping postures. The experimental results of this work indicate that the proposed algorithm can achieve high accuracy when sleep is stable and in the stage of sleep instability it can also make most of correct decisions about sleeping posture.

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Authors and Affiliations

  1. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Min Wang, Peizhi Liu & Weidong Gao

Authors
  1. Min Wang
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  2. Peizhi Liu
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  3. Weidong Gao
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Corresponding author

Correspondence to Min Wang .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Texas at Arlington, Arlington, Texas, USA

    Qilian Liang

  2. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Jiasong Mu

  3. Harbin Institute of Technology, Harbin, Heilongjiang, China

    Min Jia

  4. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Wei Wang

  5. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Xuhong Feng

  6. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Baoju Zhang

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Wang, M., Liu, P., Gao, W. (2019). Automatic Sleeping Posture Detection in Ballistocardiography. In: Liang, Q., Mu, J., Jia, M., Wang, W., Feng, X., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2017. Lecture Notes in Electrical Engineering, vol 463. Springer, Singapore. https://doi.org/10.1007/978-981-10-6571-2_216

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  • DOI: https://doi.org/10.1007/978-981-10-6571-2_216

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6570-5

  • Online ISBN: 978-981-10-6571-2

  • eBook Packages: EngineeringEngineering (R0)

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