Multi-modal Data Acquisition Platform for Behavioral Evaluation

This dataset contains multiple physiological signal modalities, including “functional near-infrared spectroscopy” (fNIRS), “electroencephalography” (EEG), pupillometry, respiration, electrodermal activity, and beat-to-beat plethysmography acquired from eighty healthy participants recruited from the local community as they drove in a realistic driving simulator. To empirically generate different levels of systemic human cognitive states, we asked the participants to complete secondary tasks while driving.

本数据集包含多模态生理信号，涵盖功能性近红外光谱（functional near-infrared spectroscopy，fNIRS）、脑电图（electroencephalography，EEG）、瞳孔测量（pupillometry）、呼吸信号（respiration）、皮肤电活动（electrodermal activity）以及逐搏光电容积描记法（beat-to-beat plethysmography）。上述信号采集自从当地社区招募的80名健康受试者，采集时段为受试者在真实驾驶模拟器中驾驶的过程中。为实证诱导不同层级的人类整体认知状态，我们要求受试者在驾驶过程中完成次级任务。