Brain's Stress Observation System Using 2-Channels NIRS Based on Classroom Activity

Kant Sunthad, Yoshihiro Niitsu, Masahiro Inoue, Taketoshi Yokemura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In classroom, teachers have a role to impart education and encourage learning to their students. More teachers are using various activities to make students keep focus on class but in the real situation teachers are facing a difficulty to make all student keep attention, because each student's mental activity and personal problem are different [1]. To improve classroom management, we proposed a method to make teachers are able to keep monitoring and analyzing student's brain stress level by using 2-channels near-infrared spectroscopy (NIRS) sensor. This paper focuses on a method for observing a brain behavior under stress based on classroom activity. The data recorded from the experiment is analyzed in order to integrate with an internet of things architecture and to adapt deep learning algorithm in future development.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Consumer Electronics, ICCE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538679104
DOIs
Publication statusPublished - 2019 Mar 6
Event2019 IEEE International Conference on Consumer Electronics, ICCE 2019 - Las Vegas, United States
Duration: 2019 Jan 112019 Jan 13

Publication series

Name2019 IEEE International Conference on Consumer Electronics, ICCE 2019

Conference

Conference2019 IEEE International Conference on Consumer Electronics, ICCE 2019
CountryUnited States
CityLas Vegas
Period19/1/1119/1/13

Keywords

  • brain activity
  • classroom activity
  • deep learning
  • internet of things
  • near-infrared spectroscopy (NIRS)
  • stress

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Media Technology
  • Electrical and Electronic Engineering

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