Eye Tracking Dataset for the 12-Lead Electrocardiogram Interpretation of Medical Practitioners and Students

This dataset contains collected eye tracking data from medical practitioners and students with different expertise levels to understand their electrocardiogram interpretation behavior. These medical practitioners encounter electrocardiograms during their daily medical practice. The end goal of the collection of this dataset was to use it for analysis to uncover insights about key best practices as well as pitfall in the ECG interpretation process. The data consists of quantitative eye tracking measurements for different eye gaze features for 63 participants. These participants belong to six expertise categories, namely: medical students, nurses, technicians, residents, fellows and finally consultants. Each one of these participants contributed to the data collection by interpreting ten different electrocardiograms. The eye tracking data includes the eye fixations count and duration, the eye gaze duration, and finally the fixations revisitations. It was collected at 60 frames per second using a Tobii Pro X2-60. Each participant was allowed a timeframe of 30 seconds to interpret each one of the ten ECGs.  The collected data was processed taking into consideration two defined area of interest distributions. This enabled the extraction of metrics specifically tailored for the 12-lead electrocardiogram.

本数据集收录了来自不同专业水平（包括医学实习生、护士、技术人员、住院医师、研究员及顾问）的医学实践者和学生的眼动追踪数据，旨在探究他们在心电图解读过程中的行为模式。这些医学实践者在日常医疗实践中都会遇到心电图。收集本数据集的最终目的是通过分析揭示心电图解读过程中的关键最佳实践及其潜在误区。数据包含63名参与者不同眼动特征的定量眼动追踪测量，这些参与者被划分为六个专业类别。每位参与者对十张不同的心电图进行了解读，以贡献数据。眼动追踪数据包括眼动固定次数和持续时间、眼动注视持续时间和最终的眼动回访。数据以每秒60帧的速率使用Tobii Pro X2-60采集。每位参与者有30秒的时间来解读每张心电图。所收集的数据经过处理，考虑了两个定义的兴趣区域分布，从而提取了专门针对12导联心电图的具体指标。