It takes two (seconds): decreasing encoding time for two-choice functional near-infrared spectroscopy brain-computer interface communication

Anna Vorreuther*, Lisa Bastian, Amaia Benitez Andonegui, Danielle Evenblij, Lars Riecke, Michael Lührs, Bettina Sorger

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

SIGNIFICANCE: Brain-computer interfaces (BCIs) can provide severely motor-impaired patients with a motor-independent communication channel. Functional near-infrared spectroscopy (fNIRS) constitutes a promising BCI-input modality given its high mobility, safety, user comfort, cost-efficiency, and relatively low motion sensitivity. AIM: The present study aimed at developing an efficient and convenient two-choice fNIRS communication BCI by implementing a relatively short encoding time (2 s), considerably increasing communication speed, and decreasing the cognitive load of BCI users. APPROACH: To encode binary answers to 10 biographical questions, 10 healthy adults repeatedly performed a combined motor-speech imagery task within 2 different time windows guided by auditory instructions. Each answer-encoding run consisted of 10 trials. Answers were decoded during the ongoing experiment from the time course of the individually identified most-informative fNIRS channel-by-chromophore combination. RESULTS: The answers of participants were decoded online with an accuracy of 85.8% (run-based group mean). Post-hoc analysis yielded an average single-trial accuracy of 68.1%. Analysis of the effect of number of trial repetitions showed that the best information-transfer rate could be obtained by combining four encoding trials. CONCLUSIONS: The study demonstrates that an encoding time as short as 2 s can enable immediate, efficient, and convenient fNIRS-BCI communication.
Original languageEnglish
Article number045005
JournalNeurophotonics
Volume10
Issue number4
DOIs
Publication statusPublished - 2 Nov 2023

Keywords

  • brain-based communication
  • brain–computer interface
  • fNIRS
  • mental imagery
  • motor disability
  • online data analysis
  • “locked-in” syndrome

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