Journal of Advanced Information Technology and Convergence (한국정보기술학회 영문논문지)

Korean Institute of Information Technology (한국정보기술학회)
권호 표지
DOI QR코드

DOI QR Code

State Analysis and Location Tracking Technology through EEG and Position Data Analysis

  • Jo, Guk-Han (Department of Electronic Engineering, Kumoh National Institute of Technology) ;
  • Song, Young-Joon (Department of Electronic Engineering, Kumoh National Institute of Technology)
  • Received : 2018.12.03
  • Accepted : 2018.12.22
  • Published : 2018.12.31
⟨ Previous Next ⟩

Abstract

In this paper, we describe the algorithms, EEG classification methods, and position data analysis methods using EEG and ADS1299 sensors. In addition, it is necessary to manage the amount of real-time data of location data and EEG data and to extract data efficiently. To do this, we explain the process of extracting important information from a vast amount of data through a cloud server. The electrical signals extracted from the brain are measured to determine the psychological state and health status, and the measured positions can be collected using the position sensor and triangulation method.

Keywords

Acknowledgement

Supported by : IITP(Institute for Information & communications Technology Promotion)

References

  1. Guk-Han Jo and Young-Joon Song, "EEG and Position Analysis using Cloud Sharing System", Advanced Science and Technology Letters, NGCIT, Vol. 152, pp.156-159, 2018.
  2. Seo Hwa Jeong and Kim Ho Won, "Optimized implementation of HIGHT algorithm for sensor network", The journal of the Korea Institute of Maritime Information & Communication Sciences, Vol. 15, No. 7, pp. 1510-1516, Jun 2011. https://doi.org/10.6109/jkiice.2011.15.7.1510
  3. G. Han Jo, "Sensor Data Analysis and Visualiization of IoT System for Combat Helmet", Advanced Science Letters, Vol. 23, No. 10 pp. 10342-10345, Oct. 2017. https://doi.org/10.1166/asl.2017.10448
  4. Ilyoung Kim and Goangseog Choi, "Indoor Location-aware System Development using RSSI Handover Technique", The journal of Korean institute of next generation computing, Vol. 7, No. 3, pp. 39-46, Jun 2011.
  5. Ryota Tazawa1, Naoki Honma1, Miura Atsusi and Minamizawa Hiroto, "Improving Accuracy of RSSI-Based Indoor Localization Using Three-Element Array", International Symposium on Antennas and Propagation, pp. 336-337, Oct. 2016.
  6. Lee Byoungsu and Kim Seunwoo, "A Study on Self-Localization of Home Wellness Robot Using Collaboration of Trilateration and Triangulation", Journal of IEEE Korea Council, Vol. 18, No. 1, pp. 57-63, May 2014.
  7. Yapeng Wang, Xu Yang, Yutian Zhao and Yue Liu, Laurie Cuthbert, "Bluetooth Positioning using RSSI and Triangulation Methods", IEEE 10th Consumer Communications and Networking Conference, Las Vegas, NV, USA, Jan. 2013, pp. 837-842.
  8. C. H. Lee, J. W. Kim, G.D. Kim, J. E. Hong, D. S. Shin, and D. H. Lee, "A Study on EEG based Concentration Transmission and Brain Computer Interface Application", Journal of the Institute of Electronics Engineers of Korea, Vol. 46, No. 2, pp. 41-46, Mar. 2009.
  9. Dan Nie, Xiao-Wei Wang, Li-Chen Shi, and Bao-Liang Lu Senior Member, "EEG-based Emotion Recognition during Watching Movies", Proceedings of the 5th International IEEE EMBS Conference on Neural Engineering, Cancun, Mexico, 2011, pp. 667-670.
  10. Ho Duc Kim and Kwee Bo Sim, "Brain-wave Analysis using fMRI, TRS and EEG for Human Emotion Recognition", Journal of Korean institute of intelligent systems, Vol. 17, No. 6, pp. 832-837, Dec. 2007. https://doi.org/10.5391/JKIIS.2007.17.6.832