Brainsourcing: Crowdsourcing Recognition Tasks via Collaborative Brain-Computer Interfacing
| Autor: | Lauri Kangassalo, Michiel M. Spapé, Tuukka Ruotsalo, Keith M. Davis |
|---|---|
| Přispěvatelé: | Department of Computer Science, Department of Psychology and Logopedics |
| Rok vydání: | 2020 |
| Předmět: |
Class (computer programming)
medicine.diagnostic_test Computer science business.industry education 05 social sciences 020207 software engineering 02 engineering and technology Electroencephalography 113 Computer and information sciences Crowdsourcing Task (project management) Human–computer interaction 0202 electrical engineering electronic engineering information engineering medicine 0501 psychology and cognitive sciences F1 score Set (psychology) business 050107 human factors |
| Zdroj: | CHI |
| DOI: | 10.1145/3313831.3376288 |
| Popis: | This paper introduces brainsourcing: utilizing brain responses of a group of human contributors each performing a recognition task to determine classes of stimuli. We investigate to what extent it is possible to infer reliable class labels using data collected utilizing electroencephalography (EEG) from participants given a set of common stimuli. An experiment (N=30) measuring EEG responses to visual features of faces (gender, hair color, age, smile) revealed an improved F1 score of 0.94 for a crowd of twelve participants compared to an F1 score of 0.67 derived from individual participants and a random chance of 0.50. Our results demonstrate the methodological and pragmatic feasibility of brainsourcing in labeling tasks and opens avenues for more general applications using brain-computer interfacing in a crowdsourced setting. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|