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An EOG-Based Automatic Sleep Scoring System and Its Related Application in Sleep Environmental Control

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Physiological Computing Systems (PhyCS 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8908))

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Abstract

Human beings spend approximately one third of their lives sleeping. Conventionally, to evaluate a subjects sleep quality, all-night polysomnogram (PSG) readings are taken and scored by a well-trained expert. Unlike a bulky PSG or EEG recorder on the head, the development of an electrooculogram (EOG)-based automatic sleep-staging system will enable physiological computing systems (PhyCS) to progress toward easy sleep and comfortable monitoring. In this paper, an EOG-based sleep scoring system is proposed. EOG signals are also coupling some of sleep characteristics of EEG signals. Compared to PSG or EEG recordings, EOG has the advantage of easy placement, and can be operated by the user individually at home. The proposed method was found to be more than 83 % accurate when compared with the manual scorings applied to sixteen subjects. In addition to sleep-quality evaluation, the proposed system encompasses adaptive brightness control of light according to online monitoring of the users sleep stages. The experiments show that the EOG-based sleep scoring system is a practicable solution for homecare and sleep monitoring due to the advantages of comfortable recording and accurate sleep staging.

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Acknowledgements

This work was supported by the National Science Council of Taiwan under Grants NSC 102-2221-E-009-082-MY3, 100-2410-H-006-025-MY3, and 1102-2220-E-006-001. Moreover, this paper was also supported by “Aiming for the Top University Program” of the National Chiao Tung University and Ministry of Education,Taiwan, R.O.C.

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Authors and Affiliations

  1. The Institute of Cognitive Science, National Cheng Kung University, Tainan, Taiwan

    Chih-En Kuo & Fu-Zen Shaw

  2. Department of Computer Science, National Chiao Tung University, Tainan, Taiwan

    Yi-Chieh Lee, Fu-Yin Cherng & Wen-Chieh Lin

  3. Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan

    Sheng-Fu Liang, Peng-Yu Chen & Yen-Chen Liu

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  1. Chih-En Kuo
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Correspondence to Chih-En Kuo .

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Editors and Affiliations

  1. IT - Instituto de Telecomunicações, Lisbon, Portugal

    Hugo Plácido da Silva

  2. Medical University Graz, Graz, Austria

    Andreas Holzinger

  3. Liverpool John Moores, Liverpool, Merseyside, United Kingdom

    Stephen Fairclough

  4. ETH Zurich, Zurich, Switzerland

    Dennis Majoe

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Kuo, CE. et al. (2014). An EOG-Based Automatic Sleep Scoring System and Its Related Application in Sleep Environmental Control. In: da Silva, H., Holzinger, A., Fairclough, S., Majoe, D. (eds) Physiological Computing Systems. PhyCS 2014. Lecture Notes in Computer Science(), vol 8908. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45686-6_5

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  • DOI: https://doi.org/10.1007/978-3-662-45686-6_5

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