Experimental Brain Research

, Volume 232, Issue 2, pp 555–564 | Cite as

Online binary decision decoding using functional near-infrared spectroscopy for the development of brain–computer interface

  • Noman Naseer
  • Melissa Jiyoun Hong
  • Keum-Shik HongEmail author
Research Article


In this paper, a functional near-infrared spectroscopy (fNIRS)-based online binary decision decoding framework is developed. Fourteen healthy subjects are asked to mentally make “yes” or “no” decisions in answers to the given questions. For obtaining “yes” decoding, the subjects are asked to perform a mental task that causes a cognitive load on the prefrontal cortex, while for making “no” decoding, they are asked to relax. Signals from the prefrontal cortex are collected using continuous-wave near-infrared spectroscopy. It is observed and verified, using the linear discriminant analysis (LDA) and the support vector machine (SVM) classifications, that the cortical hemodynamic responses for making a “yes” decision are distinguishable from those for making a “no” decision. Using mean values of the changes in the concentration of hemoglobin as features, binary decisions are classified into two classes, “yes” and “no,” with an average classification accuracy of 74.28 % using LDA and 82.14 % using SVM. These results demonstrate and suggest the feasibility of fNIRS for a brain–computer interface.


Binary decision decoding Functional near-infrared spectroscopy Brain–computer interface Yes/no decoding 



This research was supported by the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology, Republic of Korea (Grant No. MEST-2012-R1A2A2A01046411).

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Noman Naseer
    • 1
  • Melissa Jiyoun Hong
    • 2
  • Keum-Shik Hong
    • 1
    • 3
    Email author
  1. 1.Department of Cogno-Mechatronics EngineeringPusan National UniversityBusanKorea
  2. 2.Department of Education Policy and Social AnalysisColumbia UniversityNew YorkUSA
  3. 3.School of Mechanical EngineeringPusan National UniversityBusanKorea

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