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.