Authors:
Chih-En Kuo
1
;
Sheng-Fu Liang
1
;
Yi-Chieh Li
2
;
Fu-Yin Cherng
2
;
Wen-Chieh Lin
2
;
Peng-Yu Chen
1
;
Yen-Chen Liu
1
and
Fu-Zen Shaw
1
Affiliations:
1
National Cheng Kung University, Taiwan
;
2
National Chiao Tung University, Taiwan
Keyword(s):
Sleep, Sleep Stage, Adaptive System, Electrooculogram (EOG), Interaction Design, Sleep Quality.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Biomedical Devices for Computer Interaction
;
Biomedical Engineering
;
Biomedical Instruments and Devices
;
Biomedical Signal Processing
;
Biosignal Acquisition, Analysis and Processing
;
Devices
;
Health Information Systems
;
Health Monitoring Devices
;
Human-Computer Interaction
;
Interactive Physiological Systems
;
Methodologies and Methods
;
Pattern Recognition
;
Physiological Computing Systems
;
Software Engineering
;
Wearable Sensors and Systems
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. The
development of an automatic sleep-staging system that does not rely upon mounting a bulky PSG or EEG
recorder on the head will enable physiological computing systems (PhyCS) to progress toward easy sleep and
comfortable monitoring. In this paper, an electrooculogram (EOG)-based sleep scoring system is proposed.
Compared to PSG or EEG recordings, EOG has the advantage of easy placement, and can be operated by
the user individually. 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 sy
stem is a practicable solution for home-use sleep
monitoring due to the advantages of comfortable recording and accurate sleep staging.
(More)