title: A hybrid NIRS-EEG system for self-paced brain computer interface with online motor imagery.
abstract: BACKGROUND
  For a self-paced motor imagery based brain-computer interface (BCI), the system should be able to recognize the occurrence of a motor imagery, as well as the type of the motor imagery. However, because of the difficulty of detecting the occurrence of a motor imagery, general motor imagery based BCI studies have been focusing on the cued motor imagery paradigm.
  
  
  METHODS
  In this paper, we present a novel hybrid BCI system that uses near infrared spectroscopy (NIRS) and electroencephalography (EEG) systems together to achieve online self-paced motor imagery based BCI. We designed a unique sensor frame that records NIRS and EEG simultaneously for the realization of our system. Based on this hybrid system, we proposed a novel analysis method that detects the occurrence of a motor imagery with the NIRS system, and classifies its type with the EEG system.
  
  
  RESULTS
  An online experiment demonstrated that our hybrid system had a true positive rate of about 88%, a false positive rate of 7% with an average response time of 10.36 s.
  
  
  CONCLUSIONS
  As far as we know, there is no report that explored hemodynamic brain switch for self-paced motor imagery based BCI with hybrid EEG and NIRS system.
  
  
  CONCLUSIONS
  From our experimental results, our hybrid system showed enough reliability for using in a practical self-paced motor imagery based BCI.
authors.affiliation: School of Interdisciplinary Bioscience and Bioengineering, POSTECH, Republic of Korea. Electronic address: bkkoo@postech.ac.kr.
authors.forename: Bonkon
authors.initials: B
authors.lastname: Koo
authors.affiliation: Department of Physical Education, Hallym University, Chuncheon, Republic of Korea. Electronic address: lfgon75@gmail.com.
authors.forename: Hwan-Gon
authors.initials: HG
authors.lastname: Lee
authors.affiliation: School of Interdisciplinary Bioscience and Bioengineering, POSTECH, Republic of Korea. Electronic address: druid@postech.ac.kr.
authors.forename: Yunjun
authors.initials: Y
authors.lastname: Nam
authors.affiliation: Department of Computer Science and Engineering, POSTECH, Republic of Korea. Electronic address: paanguin@postech.ac.kr.
authors.forename: Hyohyeong
authors.initials: H
authors.lastname: Kang
authors.affiliation: Department of Physiology, College of Medicine, Hallym University, Chuncheon, Republic of Korea. Electronic address: chris77@hallym.ac.kr.
authors.forename: Chin Su
authors.initials: CS
authors.lastname: Koh
authors.affiliation: Department of Physiology, College of Medicine, Hallym University, Chuncheon, Republic of Korea. Electronic address: hcshin@hallym.ac.kr.
authors.forename: Hyung-Cheul
authors.initials: HC
authors.lastname: Shin
authors.affiliation: Department of Computer Science and Engineering, POSTECH, Republic of Korea. Electronic address: seungjin@postech.ac.kr.
authors.forename: Seungjin
authors.initials: S
authors.lastname: Choi
mesh_terms: D000328:Adult; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D058256:Brain Waves / Q000502:physiology*; D062207:Brain-Computer Interfaces; D004569:Electroencephalography; D006454:Hemoglobins / Q000378:metabolism*; D006801:Humans; D007092:Imagination / Q000502:physiology*; D008297:Male; D009068:Movement; D009862:Online Systems; D000068356:Self-Control; D019265:Spectroscopy, Near-Infrared; D055815:Young Adult
chemical_list: D006454:Hemoglobins
keywords: Electroencephalogram (EEG); Hybrid brain–computer interface (BCI); Motor imagery based BCI; Near infrared spectroscopy (NIRS); Online BCI system; Self-paced BCI