An EOG-based automatic sleep scoring system and its related application in sleep environmental control

Chih En Kuo, Sheng Fu Liang, Yi Chieh Lee, Fu Yin Cherng, Wen Chieh Lin, Peng Yu Chen, Yen Chen Liu, Fu Zen Shaw

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)71-88
Number of pages18
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8908
DOIs
Publication statusPublished - 2014

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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