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High Order Moment Features for NIRS-Based Classification Problems

  • Tuan Hoang
  • Dat Tran
  • Khoa Truong
  • Phuoc Nguyen
  • Toi Vo Van
  • Xu Huang
  • Dhamendra Sharma
Part of the IFMBE Proceedings book series (IFMBE, volume 49)

Abstract

This paper aims to experiment high order moment features in two well-known problems which are motor imagery and person authentication in Brain Computer Interface (BCI) systems using Near Infrared Spectroscopy (NIRS) technique. To improve performance of the systems, we propose a new feature by combining 2nd order and 4th order moments of signal together. Our results show that such the feature not only achieves very high recall and precision ratios but also is practical for online NIRS-based BCI systems. Our systems can achieve recall and precision ratio at 99.2% for the left-hand and right-hand imagery problem, and up to 100% for the person authentication problem.

Keywords

NIRS-based BCI high order moment Brain Computer Interface motor imagery person authentication 

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Copyright information

© IFMBE 2013

Authors and Affiliations

  • Tuan Hoang
    • 1
  • Dat Tran
    • 1
  • Khoa Truong
    • 2
  • Phuoc Nguyen
    • 1
  • Toi Vo Van
    • 2
  • Xu Huang
    • 1
  • Dhamendra Sharma
    • 1
  1. 1.Faculty of Information Sciences and EngineeringUniversity of CanberraCanberraAustralia
  2. 2.Department of Biomedical EngineeringHCMC International UniversityHo Chi Minh CityVietnam

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