SynthesisEuropean journal of medical research2025
A systematic review of eye-tracking technology in electrocardiogram interpretation research.
Synthesis in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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7 authors.
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Abstract
backgroundEye-tracking technology provides an objective method for analyzing visual behavior during diagnostic tasks such as electrocardiogram (ECG) interpretation. As a high-stakes and visually complex clinical skill, ECG interpretation benefits from technologies that differentiate experts from novices via gaze patterns. We systematically reviewed eye-tracking in ECG research to examine links between gaze metrics and diagnostic performance and to appraise educational applications.
methodsFollowing PRISMA (PROSPERO CRD420251052940), we searched PubMed, Embase, Web of Science, Scopus, ERIC, IEEE Xplore, and PubPsych databases to September 2025. Eligible studies used eye-tracking during ECG interpretation and reported visual behavior or diagnostic outcomes. Two independent reviewers performed the study selection, data extraction, and quality assessment using the Jadad and Newcastle-Ottawa scales. Given heterogeneity, we conducted a narrative synthesis.
resultsNineteen studies (573 participants) were included, mainly involving students or early-career clinicians. Common metrics included fixation duration, counts, time to first fixation, and scan-path efficiency. Experts showed faster, more targeted fixation on critical leads (V1, V2, and II), shorter interpretation times, and higher accuracy. Novices exhibited scattered visual behavior and delayed attention to diagnostically relevant regions. Eye movement data were informative of underlying cognitive processes, including the selection, organization, and integration of ECG features. Additional factors, such as presentation format, individual experience, metacognitive strategies, and emotional responses, may moderate gaze behavior, although these were underexplored. Educational interventions leveraging expert gaze modeling or structured checklists showed mixed but promising outcomes.
conclusionsEye-tracking differentiates expertise in ECG interpretation and may inform diagnostic reasoning, but prospective validation is needed. Gaze metrics are candidate indicators of performance and a foundation for feedback-based educational tools. Standardized protocols, larger multi-site studies, and inclusion of diverse learners are required to realize the potential of eye-tracking in ECG training and assessment.
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