Collaborative Brain-Computer Interfaces to Enhance Group Decisions in an Outpost Surveillance Task

Saugat Bhattacharyya, Davide Valeriani, Caterina Cinel, Luca Citi, Riccardo Poli

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)
151 Downloads (Pure)


We present a two-layered collaborative Brain-Computer Interface (cBCI) to aid groups making decisions under time constraints in a realistic video surveillance setting - the very first cBCI application of this type. The cBCI first uses response times (RTs) to estimate the decision confidence the user would report after each decision. Such an estimate is then used with neural features extracted from EEG to refine the decision confidence so that it better correlates with the correctness of the decision. The refined confidence is then used to weigh individual responses and obtain group decisions. Results obtained with 10 participants indicate that cBCI-assisted groups are significantly more accurate than groups using standard majority or weighing decisions using reported confidence values. This two-layer architecture allows the cBCI to not only further enhance group performance but also speed up the decision process, as the cBCI does not have to wait for all users to report their confidence after each decision.
Original languageEnglish
Title of host publication2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Place of PublicationBerlin, Germany
Number of pages4
Publication statusPublished (in print/issue) - 7 Oct 2019


  • brain computer interface
  • collaborative decision-making
  • Group decision making
  • Reported Confidence Estimation
  • Realistic and Dynamic Environment


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