ROSbag-based Multimodal Affective Dataset for Emotional and Cognitive States
作者： Wonse Jo , Shyam Sundar Kannan , Go-Eum Cha , Ahreum Lee , Byung-Cheol Min
DOI: 10.1109/SMC42975.2020.9283320
关键词:
摘要: This paper introduces a new ROSbag-based multimodal affective dataset for emotional and cognitive states generated using the Robot Operating System (ROS). We utilized images sounds from International Affective Pictures (IAPS) Digitized Sounds (IADS) to stimulate targeted emotions (happiness, sadness, anger, fear, surprise, disgust, neutral), dual N-back game different levels of workload. 30 human subjects participated in user study; their physiological data were collected latest commercial wearable sensors, behavioral hardware devices such as cameras, subjective assessments carried out through questionnaires. All stored single ROSbag files rather than conventional Comma-Separated Values (CSV) files. not only ensures synchronization signals videos set, but also allows researchers easily analyze verify algorithms by connecting directly this ROS. The consists 1,602 files, size is about 787GB. made publicly available. expect that our can be great resource many fields computing, Human-Computer Interaction (HCI), Human-Robot (HRI).
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