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International Conference on 5G for Future Wireless Networks

5GWN 2019: 5G for Future Wireless Networks pp 43–59Cite as

Smartphone-Based Intelligent Sleep Monitoring

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Abstract

The sleeping quality is one of the most important factors to judge people’s health status, and has drawn increasing attention of the public recently. However, the quantified results of sleeping quality can generally be achieved in labs with the help of high precision instrument, such as Actigraphy or professional graph like Polysomnography (PSG), and are thus not available for the general public. In this paper, we construct a novel way of sleep-scoring system implanted in the iSmile app. iSmile first collects the sounds recorded by smart phone recorder, then classifies the sound frames with a light weight decision tree algorithm. Based on the number and the average amplitude of sleep-related events, we score the users’ sleeping quality in three aspects (respectively cough-score, snore-score and talk-score) using Pittsburgh Sleep Quality Index (PSQI) and Pediatric Sleep Questionnaire (PSQ). During users’ sleeping period, iSmile also collects data from the accelerator sensor to predict the users’ mood (presented in valence and arousal) and recommend smart alarm sounds to help improve their mood. For the experiment, we involved 5 participants (20 nights in total) and achieved high precision of predicting sleep events (above 89%), with the users’ valence and arousal improved by 14.57%. From succinct chart of sleeping score on the App UI, users can see the visualized results of their sleeping quality.

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Author information

Authors and Affiliations

  1. Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China

    Pansheng Fang & Xiping Hu

  2. School of Electronic and Information Engineering, South China University of Technology, Guangzhou, 510641, China

    Pansheng Fang

  3. School of Software, Dalian University of Technology, Dalian, 116620, China

    Zhaolong Ning

Authors
  1. Pansheng Fang
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  2. Zhaolong Ning
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  3. Xiping Hu
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Corresponding author

Correspondence to Pansheng Fang .

Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC, Canada

    Victor C. M. Leung

  2. University of Science and Technology, Beijing, China

    Haijun Zhang

  3. Shenzhen University, Shenzhen, China

    Xiping Hu

  4. National University of Defense Technology, Changsha, China

    Qiang Liu

  5. Shizuoka University, Shizuoka, Japan

    Zhi Liu

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

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Fang, P., Ning, Z., Hu, X. (2019). Smartphone-Based Intelligent Sleep Monitoring. In: Leung, V., Zhang, H., Hu, X., Liu, Q., Liu, Z. (eds) 5G for Future Wireless Networks. 5GWN 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 278. Springer, Cham. https://doi.org/10.1007/978-3-030-17513-9_4

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  • DOI: https://doi.org/10.1007/978-3-030-17513-9_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-17512-2

  • Online ISBN: 978-3-030-17513-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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