title: Towards a ternary NIRS-BCI: single-trial classification of verbal fluency task, Stroop task and unconstrained rest.
abstract: OBJECTIVE
  The majority of near-infrared spectroscopy (NIRS) brain-computer interface (BCI) studies have investigated binary classification problems. Limited work has considered differentiation of more than two mental states, or multi-class differentiation of higher-level cognitive tasks using measurements outside of the anterior prefrontal cortex. Improvements in accuracies are needed to deliver effective communication with a multi-class NIRS system. We investigated the feasibility of a ternary NIRS-BCI that supports mental states corresponding to verbal fluency task (VFT) performance, Stroop task performance, and unconstrained rest using prefrontal and parietal measurements.
  
  
  METHODS
  Prefrontal and parietal NIRS signals were acquired from 11 able-bodied adults during rest and performance of the VFT or Stroop task. Classification was performed offline using bagging with a linear discriminant base classifier trained on a 10 dimensional feature set.
  
  
  RESULTS
  VFT, Stroop task and rest were classified at an average accuracy of 71.7% ± 7.9%. The ternary classification system provided a statistically significant improvement in information transfer rate relative to a binary system controlled by either mental task (0.87 ± 0.35 bits/min versus 0.73 ± 0.24 bits/min).
  
  
  CONCLUSIONS
  These results suggest that effective communication can be achieved with a ternary NIRS-BCI that supports VFT, Stroop task and rest via measurements from the frontal and parietal cortices. Further development of such a system is warranted. Accurate ternary classification can enhance communication rates offered by NIRS-BCIs, improving the practicality of this technology.
authors.affiliation: Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, 150 Kilgour Road, Toronto, Ontario, M4G 1R8, Canada. Institute of Biomaterials and Biomedical Engineering, University of Toronto, 164 College Street, Toronto, Ontario, M5S 3G9, Canada.
authors.forename: Larissa
authors.initials: L
authors.lastname: C Schudlo
authors.forename: Tom
authors.initials: T
authors.lastname: Chau
mesh_terms: D000328:Adult; D062207:Brain-Computer Interfaces; D005260:Female; D006801:Humans; D008297:Male; D010296:Parietal Lobe / Q000502:physiology; D017397:Prefrontal Cortex / Q000502:physiology; D011597:Psychomotor Performance / Q000502:physiology*; D011930:Reaction Time / Q000502:physiology; D012146:Rest / Q000502:physiology*; D019265:Spectroscopy, Near-Infrared / Q000379:methods*; D013060:Speech / Q000502:physiology*; D057190:Stroop Test; D055815:Young Adult