BIRAFFE: Bio-Reactions and Faces for Emotion-based Personalization

We present <strong>BIRAFFE</strong>, a dataset consisting of <em><strong>electrocardiogram (ECG)</strong></em>, <em><strong>galvanic skin reaction (GSR)</strong></em> and changes in <em><strong>facial expression</strong></em> signals recorded during affect elicitation by means of <em><strong>audio-visual stimuli</strong></em> (from IADS and IAPS databases) and our two proof-of-concept <em><strong>affective games</strong></em> ("Affective SpaceShooter 2" and "Fred Me Out 2"). 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>subjects' self-assessment</strong></em> of their affective state after each stimuli (with the use of two widgets: the first one with <em><strong>5 emoticons</strong></em> and the second with <em><strong>valence and arousal</strong></em> dimensions) and <em><strong>"Big Five" personality traits</strong></em> assessment (using NEO-FFI inventory). For detailed description see <em>BIRAFFE-AfCAI2019-paper.pdf</em>.<br> For preview of the files before downloading the whole dataset see <em>sample-SUB1107-[...]</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., Jemioło, P., Bobek, S., Giżycka, B., Rodriguez-Fernandez, V., &amp; Nalepa, G. J. (2020). "BIRAFFE: Bio-Reactions and Faces for Emotion-based Personalization". In G. J. Nalepa, J. M. Ferrandez, J. Palma, &amp; V. Julian (Eds.), Proceedings of the 3rd Workshop on Affective Computing and Context Awareness in Ambient Intelligence (AfCAI 2019) (CEUR-WS Vol. 2609). http://ceur-ws.org/Vol-2609/ Our research related to the BIRAFFE dataset is summarized in:<br> Kutt, K., Drążyk, D., Bobek, S., &amp; Nalepa, G. J. (2021). "Personality-Based Affective Adaptation Methods for Intelligent Systems". Sensors, 21(1), 163. https://doi.org/10.3390/s21010163

我们提出了<strong>BIRAFFE</strong>数据集，该数据集包含通过视听刺激（取自IADS与IAPS数据库）以及我们两款概念验证型情感游戏《Affective SpaceShooter 2》与《Fred Me Out 2》诱发情感过程中采集的心电图（electrocardiogram, ECG）、皮肤电反应（galvanic skin reaction, GSR）以及面部表情变化信号。所有信号均采用便携低成本设备采集：针对ECG与GSR信号使用BITalino (r)evolution套件，面部图像采集则采用Creative Live!网络摄像头（后续通过微软面部API（MS Face API）进行分析）。除上述信号外，本数据集还包含受试者在每次刺激后对自身情感状态的自我评估：采用两类评估组件，其一为5个表情符号量表，其二为效价与唤醒度维度量表；同时包含基于NEO-FFI量表的‘大五’人格特质（Big Five personality traits）评估。详细描述请参阅<em>BIRAFFE-AfCAI2019-paper.pdf</em>。<br>若需在下载完整数据集前预览文件，请查看<em>sample-SUB1107-[...]</em>系列文件。所有使用BIRAFFE数据集开展研究并发表相关成果的论文与文档，均需通过<strong>引用下述文献</strong>进行致谢：<br>Kutt, K., Drążyk, D., Jemioło, P., Bobek, S., Giżycka, B., Rodriguez-Fernandez, V. 及 Nalepa, G. J. (2020)。《BIRAFFE: 用于基于情感的个性化服务的生物反应与面部信号》。收录于 G. J. Nalepa、J. M. Ferrandez、J. Palma 及 V. Julian 主编，《第三届环境智能中的情感计算与情境感知研讨会（AfCAI 2019）论文集》（CEUR-WS 第2609卷）。http://ceur-ws.org/Vol-2609/<br>我们针对BIRAFFE数据集的相关研究总结于：<br>Kutt, K., Drążyk, D., Bobek, S. 及 Nalepa, G. J. (2021)。《面向智能系统的基于人格的情感自适应方法》。《传感器》，21(1)，第163页。https://doi.org/10.3390/s21010163