Development of an EOG-Based Automatic Sleep-Monitoring Eye Mask

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

64 Scopus citations


Health care researchers have recently developed several home-based sleep monitoring systems and mobile applications that support healthy sleep by monitoring a user's sleep environment, activities, or sleep quality. This study describes the design and evaluation of an electrooculogram (EOG)-based system for an automatic sleep monitoring. Compared with polysomnogram or electroencephalogram recordings, EOG has the advantage of easy placement and can be operated by the users themselves. We also design an intelligent eye mask that is user friendly for measuring sleep stage and quality. Two user experiments were carried out to demonstrate that the proposed system produces valid measurements of sleep stage and sleep quality and has good usability and reliability while not disturbing sleep significantly. These findings suggest that our system can also be applied to long-term sleep monitoring or sleep environment control to improve the user's sleep quality and make sleep more comfortable.

Original languageEnglish
Article number7115946
Pages (from-to)2977-2985
Number of pages9
JournalIEEE Transactions on Instrumentation and Measurement
Issue number11
StatePublished - 1 Nov 2015


  • Automatic sleep-scoring method
  • electrooculogram (EOG)
  • home-based sleep monitoring device
  • online


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