CogPilot

该数据集名为CogPilot，包含了35名参与者在虚拟现实中执行不同难度飞行任务时收集的多模态生理记录。这些记录涵盖了9种生理信号模态，包括肌电图（EMG）、光电容积描记图（PPG）、皮肤电活动（EDA）、心电图（ECG）、呼吸（RES）、加速度计（ACC）、陀螺仪（GD）、位置探测器（PD）和眼动追踪（EO）。所有记录的信号都通过Lab Streaming Layer进行了时间同步，以支持多模态分析。该数据集的分析基于20名拥有完整模态的受试者。研究任务是基于生理信号对飞行任务的难度等级进行分类。This dataset, named CogPilot, contains multimodal physiological recordings collected from 35 participants performing flight tasks with varying difficulty levels in virtual reality. The recordings encompass 9 physiological signal modalities, including electromyography (EMG), photoplethysmography (PPG), electrodermal activity (EDA), electrocardiography (ECG), respiration (RES), accelerometer (ACC), gyroscope (GD), position detector (PD), and eye tracking (EO). All recorded signals were temporally synchronized via Lab Streaming Layer to support multimodal analysis. Analyses of this dataset are based on 20 participants with complete signal modalities. The core research task is to classify the difficulty levels of flight tasks based on physiological signals.

搜集汇总

背景与挑战

背景概述

CogPilot数据集是一个多模态生理监测数据集，包含35名参与者在执行虚拟现实飞行任务时收集的生理、飞行性能和用户交互数据。数据涵盖四个难度级别，通过多种传感器同步记录，旨在支持算法开发以评估飞行员绩效与生理状态的关系。