Benchmark EEG data set for trust assessment for interactions with social robots

The data collection consisted of a game interaction with a small humanoid EZ-robot. The robot explains a word to the participant either through movements depicting the concept or by verbal description. Depending on their performance, participants could "earn" or loose candy as remuneration for their participation. The dataset comprises EEG (Electroencephalography) recordings from 21 participants, gathered using Emotiv headsets. Each participant's EEG data includes timestamps and measurements from 14 sensors placed across different regions of the scalp. The sensor labels in the header are as follows: EEG.AF3, EEG.F7, EEG.F3, EEG.FC5, EEG.T7, EEG.P7, EEG.O1, EEG.O2, EEG.P8, EEG.T8, EEG.FC6, EEG.F4, EEG.F8, EEG.AF4, and Time. The EEG data provides insights into the electrical activity of the brain, offering a window into cognitive processes and emotional responses during various activities or stimuli in the form of microvolt and with a frame rate of 128 Hz. The whole data set consists of 3651124 data points for each sensor, i.e. 173863 on average for each participant (min. 128505, max. 249631). Files are named after participant numbers starting with ID01. The data has to be pre-processed making use of the information given in the details.xlsx file that contains annotations corresponding to the EEG recordings. These annotations denote the timing of different phases related to trust across the participants' interactions. Each phase is delineated by a start time and an end time, representing distinct stages of the trust-building process. All the other data (timestamps) which are outside the start and end of each phase should be considered as breaks, e.g. filling out the questionnaires. The last element is the trust score for the given phase, which is calculated on the answers in an MDMT questionnaire. The following phases have been annotated: Trust Building: This phase involves friendly initial interactions for establishing trust between participants and the robot. Situational Awareness: This phase continues to build up trust by showing situation awareness of the robot, e.g. by complimenting on the participant's fashion choice. Transparency: Trust is maintained by increased openness and clarity in communicating about the robot's abilities. Trust Violation: Trust is compromised during this phase by deliberately misleading the participant and making it impossible to answer correctly. Trust Repair: The robot shows efforts to repair trust by apologizing for the behavior in the previous stage. If you work with the data, please cite one of the article given below.本数据集采集自参与者与小型类人EZ机器人（EZ-robot）的游戏交互任务。机器人可通过动作演示概念或口头描述两种方式，向参与者讲解词汇。参与者可依据自身任务表现，获取糖果作为参与报酬。 数据集包含21名参与者的脑电（Electroencephalography, EEG）数据，采用Emotiv头戴式设备采集。每名参与者的脑电数据包含时间戳与14个分布于头皮不同区域的电极测量值，表头对应的电极标签依次为：EEG.AF3、EEG.F7、EEG.F3、EEG.FC5、EEG.T7、EEG.P7、EEG.O1、EEG.O2、EEG.P8、EEG.T8、EEG.FC6、EEG.F4、EEG.F8、EEG.AF4，以及Time（时间列）。 脑电数据以微伏为单位，采样帧率为128Hz，可反映大脑电活动，为探究各类任务或刺激下的认知过程与情绪反应提供观测窗口。全数据集单传感器共包含3651124个数据点，平均每名参与者对应173863个数据点（最小值128505，最大值249631）。 数据文件以参与者编号命名，起始编号为ID01。需结合details.xlsx文件中的标注信息进行预处理，该文件包含与脑电记录对应的事件标注。这些标注用于界定参与者交互过程中与信任构建相关的不同阶段的时间区间，每个阶段由起始时间与结束时间标识，代表信任建立流程中的不同环节。所有处于各阶段起止时间之外的时间戳数据（如填写问卷时段）均视为休息间隔。此外，标注还包含基于MDMT问卷作答结果计算得到的对应阶段信任得分。 已完成标注的阶段如下： 1. 信任建立（Trust Building）：该阶段包含友好的初始交互，用于建立参与者与机器人之间的信任关系。 2. 情境感知（Situational Awareness）：该阶段通过展现机器人的情境感知能力进一步强化信任，例如称赞参与者的穿搭选择。 3. 透明度（Transparency）：通过提升沟通的开放性与清晰度，说明机器人的功能，以维持现有信任水平。 4. 信任破坏（Trust Violation）：该阶段通过故意误导参与者，使其无法正确作答，从而破坏既有的信任关系。 5. 信任修复（Trust Repair）：机器人就前一阶段的不当行为致歉，展现出修复信任的努力。 若使用本数据集开展研究，请引用下述相关论文。