한국전자통신학회논문지 (The Journal of the Korea institute of electronic communication sciences)

한국전자통신학회 (Korea Institute of Electronic Communication Science)
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건-슈팅 게임을 응용한 집중력 뉴로피드백 게임 구현

Implement Concentration Neuro-Feedback Game using Gun-Shooting Game

  • 김형민 (서울과학기술대학교 대학원) ;
  • 이대니얼주헌 (서울과학기술대학교 대학원) ;
  • 박소연 (서울과학기술대학교 대학원) ;
  • 김성권 (서울과학기술대학교 전자IT미디어공학과)
  • 투고 : 2020.01.29
  • 심사 : 2020.04.15
  • 발행 : 2020.04.30
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⟨ 이전 논문 다음 논문 ⟩

초록

뉴로피드백(Neuro feedback)은 자신의 뇌 상태를 파악하고, 뇌 상태를 의도적으로 변화시킬 수 있다는 기술로, 주의력 결핍 및 과잉 행동 장애를 겪는 사람에게 그 필요성이 대두됨에도 불구하고, 기존의 뉴로피드백 훈련은 정적인 상태를 장시간 유지하며 흥미를 주지 못하는 문제가 있었다. 따라서, 본 논문에서는 집중력 강화를 위하여 뉴로피드백과 건-슈팅 게임을 결합하는 뉴로피드백 게임을 제안 및 구현하였다. 뇌파 측정 시스템, 게임제어기 그리고 게임소프트의 설계로 뉴로피드백 게임이 구현되었으며, 본 연구로 주의력 결핍 및 과잉 행동 장애를 겪는 사람에게 뉴로피드백 훈련이 유용하게 사용되기를 기대한다.

Neuro-feedback is a technology that can identify your brain state and you can intentionally change your brain state. People with attention deficit and hyperactivity disorder need this technology but existing neuro-feedback training has a problem, which is not interesting and maintains a static state for a long time. In this paper, we proposed and implemented a neuro-feedback game that combines neuro-feedback and gun-shooting games to enhance concentration training. The neuro-feedback game has been implemented with the design of EEG measurement system, game controller and gamesoft. We hope that this study will be useful for people suffering from attention deficit and hyperactivity disorder.

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참고문헌

  1. S. Kawatake, I. Torii, and N. Ishii, "Increasing Concentration with Neurofeedback," 4th Int. Conf. on Applied Computing and Information Technology/3rd Int. Conf. on Computational Science/Intelligence and Applied Informatics/1st Int. Conf. on Big Data, Cloud Computing, Data Science & Engineering (ACIT-CSII-BCD), Las Vegas, NV, 2016, pp. 247-252.
  2. K. Yaomanee, S. Pan-ngum, and P. Ayuthaya, "Brain signal detection methodology for attention training using minimal EEG channels," Tenth Int. Conf. on ICT and Knowledge Engineering, Bangkok, 2012, pp. 84-89.
  3. K. Kim, S. Kim, H. Lim, D. Choi, and Y. Son, "Research of Advertising Management System in video platform based on Analysis using EEG," In Proc. the Korea Institute of Electronic Communication Science, Gwangju, 2019, pp. 30-33.
  4. Y. Jang, "Analysis of Concentration-Related EEG Component Due to Smartphone," J. of the Korea Institute of Electronic Communication Science, vol. 11, no. 7, 2016, pp. 717-722. https://doi.org/10.13067/JKIECS.2016.11.7.717
  5. Korean EEG Study Group, Techniques and Applications of EEG Analysis: From basics to Clinical Researches. Seoul: Medbook 2017.
  6. D. Han, M. Lee, J. Williamson, and S. Lee, "The Effect of Neurofeedback Training in Virtual and Real Environments based on BCI," 7th Int. Winter Conf. on Brain-Computer Interface (BCI), Gangwon, 2019, pp. 1-4.
  7. Y. Tong, I. Aliyu, and C. Lim, "Analysis of Dimensionality Reduction Methods Through Epileptic EEG Feature Selection for Machine Learning in BCI," J. of the Korea Institute of Electronic Communication Science, vol. 13, no. 6, 2018, pp. 1333-1342. https://doi.org/10.13067/jkiecs.2018.13.6.1333
  8. Y. Hafeez, "Investigating Neurofeedback Protocols for Stress Mitigation: A Comparative Analysis of Different Stimulus Contents," in IEEE Access, vol. 7, 2019, pp. 141021-141035. https://doi.org/10.1109/ACCESS.2019.2944202
  9. N. Sulaiman, N. Hamid, Z. Murat, and M. Taib, "Initial investigation of human physical stress level using brainwaves," IEEE Student Conf. on Research and Development (SCOReD), Serdang, 2009, pp. 230-233.
  10. T. Madan, R. Agarwal, and M. Swamy, "Compression of long-term EEG using power spectral density," The 26th Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society, San Francisco, 2004, pp. 180-183.