Design of User Concentration Classification Model by EEG Analysis Based on Visual SCPT

Jinhyeok Park; KANGSEOKHWAN; LEE BYUNGMUN; Un Gu Kang; Youngho Lee

doi:10.9708/jksci.2018.23.11.129

In this study, we designed a model that can measure the level of user's concentration by measuring and analyzing EEG data of the subjects who are performing Continuous Performance Test based on visual stimulus. This study focused on alpha and beta waves, which are closely related to concentration in various brain waves. There are a lot of research and services to enhance not only concentration but also brain activity. However, there are formidable barriers to ordinary people for using routinely because of high cost and complex procedures. Therefore, this study designed the model using the portable EEG measurement device with reasonable cost and Visual Continuous Performance Test which we developed as a simplified version of the existing CPT. This study aims to measure the concentration level of the subject objectively through simple and affordable way, EEG analysis. Concentration is also closely related to various brain diseases such as dementia, depression, and ADHD. Therefore, we believe that our proposed model can be useful not only for improving concentration but also brain disease prediction and monitoring research. In addition, the combination of this model and the Brain Computer Interface technology can create greater synergy in various fields.

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REFERENCES (16)
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* 2021년 이후 발행 논문의 참고문헌은 현재 구축 중입니다.

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