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Hybrid Collaborative Brain-Computer Interfaces to Augment Group Decision Making
| Content Provider | Semantic Scholar |
|---|---|
| Author | Valeriani, Davide Cinel, Caterina Poli, Riccardo |
| Copyright Year | 2016 |
| Abstract | © 2019 Elsevier Inc. All rights reserved. Collaborative brain-computer interfaces (cBCIs) have recently been used for neuroergonomics applications, such as improving group low-level decision-making. This chapter describes a hybrid cBCI to augment group performance in two realistic target-detection tasks: visual search, where participants had to spot a polar bear in an Arctic image including many penguins, and speech perception, where volunteers listened to audio recordings affected by noise and had to decide whether or not a target word was uttered. The cBCI aggregates individual behavioral responses according to confidence estimates obtained from neural signals and response times. Results indicate that the cBCI augments group performance in both tasks over traditional groups making decision with a standard majority. Also, cBCI groups were superior to nonBCI groups using confidence values reported by the participants to weigh decisions in visual search, although the opposite was true in speech perception. |
| Starting Page | 187 |
| Ending Page | 190 |
| Page Count | 4 |
| File Format | PDF HTM / HTML |
| DOI | 10.1016/B978-0-12-811926-6.00031-2 |
| Alternate Webpage(s) | http://repository.essex.ac.uk/19160/1/paper.pdf |
| Alternate Webpage(s) | https://doi.org/10.1016/B978-0-12-811926-6.00031-2 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
