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http://dx.doi.org/10.22156/CS4SMB.2019.9.12.008

Realtime Individual Identification based on EOG Algorithm for Customized Sleep Care Service  

Hong, Ki Hyeon (Dept. of Computer Engineering, Gachon University)
Lee, Byung Mun (Dept. of Computer Engineering, Gachon University)
Park, Yang Jae (Dept. of Computer Engineering, Gachon University)
Publication Information
Journal of Convergence for Information Technology / v.9, no.12, 2019 , pp. 8-16 More about this Journal
Abstract
Customized sleep care service needs to be provided differently for individuals since individual has different degree of sleep disorder. Because the brainwave data shows unique waveform characteristics for each person, this characteristic can be used to identify individuals. Personal identification provides an important role in enabling customized services. When you blink, you can obtain brain wave characteristics by measuring the area of the frontal lobe. Therefore, a real-time personal identification algorithm based on blinking EOG for customized sleep care service is proposed in this paper. For evaluation, 10 individuals were tested for personal identification accuracy. The results of the experiment confirmed that a maximum accuracy of 93% were taken. Algorithms can be developed by reflecting characteristics such as changes in the external environment in the future.
Keywords
EEG; EOG; Personal identification; Personalized service; Sleep care;
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Times Cited By KSCI : 2  (Citation Analysis)
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