论文标题
基于ROSBAG的情绪和认知状态的多模式情感数据集
ROSbag-based Multimodal Affective Dataset for Emotional and Cognitive States
论文作者
论文摘要
本文介绍了一个新的基于Rosbag的多模式情感数据集,用于使用机器人操作系统(ROS)生成的情绪和认知状态。我们利用国际情感图片系统(IAP)和国际情感数字化的声音(IAD)的图像和声音来刺激目标情绪(幸福,悲伤,愤怒,恐惧,惊喜,厌恶和中立),以及双n-back游戏以刺激不同水平的认知工作量。 30名人类受试者参加了用户研究;他们的生理数据是使用最新的商业可穿戴传感器收集的,使用摄像机等硬件设备收集行为数据,并通过问卷调查进行主观评估。所有数据都存储在单个ROSBAG文件中,而不是传统的逗号分隔值(CSV)文件中。这不仅可以确保数据集中的信号和视频的同步,而且还允许研究人员通过直接通过ROS连接到该数据集来轻松分析和验证其算法。生成的情感数据集由1,602个ROSBAG文件组成,数据集的大小约为787GB。该数据集可公开可用。我们希望我们的数据集可以成为情感计算,HCI和HRI领域的许多研究人员的重要资源。
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.