Lontar Komputer: Jurnal Ilmiah Teknologi Informasi
Vol 12 No 3 (2021): Vol. 12, No. 03 December 2021

Detecting Excessive Daytime Sleepiness With CNN And Commercial Grade EEG

I Putu Agus Eka Darma Udayana (STMIK STIKOM Indonesia)
Made Sudarma (Universitas Udayana)
Ni Wayan Sri Ariyani (Universitas Udayana)



Article Info

Publish Date
29 Nov 2021

Abstract

Epworth sleepiness scale is a self-assessment method in sleep medicine that has been proven to be a good predictor of obstructive sleep apnea. However, the over-reliance of the method making the process not socially distancing friendly enough in response to a global covid-19 pandemic. A study states that the Epworth sleepiness scale is correlated with the brainwave signal that commercial-grade EEG can capture. This study tried to train a classifier powered by CNN and deep learning that could perform as well as the Epworth with the objectiveness of brainwave signal. We test the classifier using the 20 university student using the Epworth sleepiness test beforehand. Then, we put the participant in 10 minutes EEG session, downsampling the data for normalization purposes and trying to predict the outcome of the ESS in respect of their brainwave state. The AI predict the reaching 65% of accuracy and 81% of sensitivity with just under 100.000 dataset which is excellent considering small dataset although this still have plenty room for improvement.

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Journal Info

Abbrev

lontar

Publisher

Subject

Computer Science & IT

Description

Lontar Komputer [ISSN Print 2088-1541] [ISSN Online 2541-5832] is a journal that focuses on the theory, practice, and methodology of all aspects of technology in the field of computer science and engineering as well as productive and innovative ideas related to new technology and information ...