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BIRAFFE2: The 2nd Study in Bio-Reactions and Faces for Emotion-based Personalization for AI Systems

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Zenodo2022-06-07 更新2026-05-25 收录
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https://zenodo.org/record/5786104
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This is our 2nd Study in Bio-Reactions and Faces for Emotion-based Personalization for AI Systems (<strong>BIRAFFE2</strong>). It is a dataset consisting of <em><strong>electrocardiogram (ECG)</strong></em>, <em><strong>galvanic skin response (GSR)</strong></em>, changes in <em><strong>facial expression</strong></em> signals and <em><strong>hand movements</strong></em> (represented by gamepad's accelerometer and gyroscope) recorded during affect elicitation by means of <em><strong>audio-visual stimuli</strong></em> (from IADS and IAPS databases) and our proof-of-concept three-level <em><strong>emotion evoking game</strong></em>. All the signals were captured using portable and low-cost equipment: BITalino (r)evolution kit for ECG and GSR and Creative Live! web camera for face photos (further analyzed by MS Face API). Besides the signals, the dataset consists also of <em><strong>participants' self-assessment</strong></em> of their affective state after each stimuli (in the <em><strong>valence and arousal dimensions</strong></em>), <em><strong>"Big Five" personality traits</strong></em> assessment (using NEO-FFI inventory), and <em><strong>game involvement</strong></em>-related metrics (using GEQ questionnaire). In 1.1.0 version, RAW questionnaire data was included. The licence was changed from CC BY-NC-ND 4.0 to CC BY 4.0. For detailed description see BIRAFFE2 Data Descriptor in Nature Scientific Data.<br> For preview of the files before downloading the whole dataset see <em>sample-SUB211-[...]</em> files. All documents and papers that report on research that uses the BIRAFFE dataset should acknowledge this by <strong>citing the paper</strong>:<br> Kutt, K., Drążyk, D., Żuchowska, L., Szelążek, M., Bobek, S., &amp; Nalepa, G. J. (2022). <strong>BIRAFFE2, a multimodal dataset for emotion-based personalization in rich affective game environments</strong>. <em>Scientific Data</em>, <em>9</em>, 274. https://doi.org/10.1038/s41597-022-01402-6
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Zenodo
创建时间:
2021-12-20
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