ROSbag-based Multimodal Affective Dataset for Emotional and Cognitive States

• URL: http://arxiv.org/abs/2006.05102v2
• Date: Tue, 20 Oct 2020 15:47:48 GMT
• Title: ROSbag-based Multimodal Affective Dataset for Emotional and Cognitive States
• Authors: Wonse Jo, Shyam Sundar Kannan, Go-Eum Cha, Ahreum Lee, and Byung-Cheol Min
• Abstract summary: This paper introduces a new ROSbag-based multimodal affective dataset for emotional and cognitive states generated using Robot Operating System (ROS) We utilized images and sounds from the International Affective Pictures System (IAPS) and the International Affective Digitized Sounds (IADS) to stimulate targeted emotions. The generated affective dataset consists of 1,602 ROSbag files, and size of the dataset is about 787GB.
• Score: 0.9786690381850356
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper introduces a new ROSbag-based multimodal affective dataset for emotional and cognitive states generated using Robot Operating System (ROS). We utilized images and sounds from the International Affective Pictures System (IAPS) and the International Affective Digitized Sounds (IADS) to stimulate targeted emotions (happiness, sadness, anger, fear, surprise, disgust, and neutral), and a dual N-back game to stimulate different levels of cognitive workload. 30 human subjects participated in the user study; their physiological data was collected using the latest commercial wearable sensors, behavioral data was collected using hardware devices such as cameras, and subjective assessments were carried out through questionnaires. All data was stored in single ROSbag files rather than in conventional Comma-separated values (CSV) files. This not only ensures synchronization of signals and videos in a data set, but also allows researchers to easily analyze and verify their algorithms by connecting directly to this dataset through ROS. The generated affective dataset consists of 1,602 ROSbag files, and size of the dataset is about 787GB. The dataset is made publicly available. We expect that our dataset can be great resource for many researchers in the fields of affective computing, HCI, and HRI.

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