Beskrivelse

The data collection consisted of a game interaction with a small humanoid EZ-robot. The robot explains a word to the participant either through movements depicting the concept or by verbal description. Depending on their performance, participants could "earn" or loose candy as remuneration for their participation. The dataset comprises EEG (Electroencephalography) recordings from 21 participants, gathered using Emotiv headsets. Each participant's EEG data includes timestamps and measurements from 14 sensors placed across different regions of the scalp. The sensor labels in the header are as follows: EEG.AF3, EEG.F7, EEG.F3, EEG.FC5, EEG.T7, EEG.P7, EEG.O1, EEG.O2, EEG.P8, EEG.T8, EEG.FC6, EEG.F4, EEG.F8, EEG.AF4, and Time.
Dato for tilgængelighed21 aug. 2024
ForlagZenodo
  • An EEG Benchmark Data Set for Data-Driven Trust Assessment in Social HRI

    Rehm, M., Pontikis, I. & Campagna, G., 2025, Social Robotics: 16th International Conference, ICSR + AI 2024, Odense, Denmark, October 23–26, 2024, Proceedings, Part II. Palinko, O., Bodenhagen, L., Cabibihan, J.-J., Fischer, K., Šabanović, S., Winkle, K., Behera, L., Ge, S. S., Chrysostomou, D., Jiang, W. & He, H. (red.). Springer, s. 360-369 10 s. (Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence subseries)).

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  • Trust Assessment with EEG Signals in Social Human-Robot Interaction

    Campagna, G. & Rehm, M., 2024, Proceedings 15th International Conference on Social Robotics (ICSR 2023). Ali, A. A., Cabibihan, J.-J., Meskin, N., Rossi, S., Jiang, W., He, H. & Ge, S. S. (red.). Springer, s. 33-42 10 s. (Lecture Notes in Computer Science).

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