# Electrocardiogram sonification accelerates detection of ST elevation myocardial infarction compared to analysis based solely on visual display: a randomized controlled simulation study with medical students

## TL;DR

Using sound to interpret heart signals helps medical students detect heart attacks faster than just looking at the signals visually.

## Contribution

This study shows that sonification of ECG signals accelerates detection of ST elevation myocardial infarction in emergency scenarios.

## Key findings

- Sonification-assisted diagnosis reduced diagnostic delay by 163 seconds compared to visual-only diagnosis.
- Individual attitudes toward sonification affected diagnostic speed within the sonification group.
- Sonification proved effective as a supplementary diagnostic tool in simulated emergency settings.

## Abstract

A 12 lead electrocardiogram (ECG) is the standard diagnostic method for the detection of an acute coronary syndrome, as it is also used in emergency medical services. A novel sonification method can convert an important part of the ECG signal into an acoustic signal: The ST segment sonification is particularly useful for the detection of transient ST elevations in patients with suspicion of acute coronary syndrome. A quick and accurate detection of transient ECG changes of the ST segment is prerequisite for proper treatment, thus having immediate therapeutic consequences.

As part of an emergency training program, a cohort of \documentclass[12pt]{minimal}
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\begin{document}$$n = 44$$\end{document} medical students was recruited to participate in a two-part study. Some of them, namely \documentclass[12pt]{minimal}
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\begin{document}$$n=32$$\end{document} of the total 44 subjects, participated in a second part of the study, an RCT, which we report on here. The diagnostic accuracy recently estimated in a classification study involving all 44 subjects with regard to acoustically presented ECG sequences of varying degrees of severity of ST-elevation myocardial infarction forms the background for the RCT described here. The \documentclass[12pt]{minimal}
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\begin{document}$$n=32$$\end{document} subjects who participated in the RCT were randomly assigned in two-person teams to either an intervention (\documentclass[12pt]{minimal}
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\begin{document}$$n=8$$\end{document} teams of two) or a control (\documentclass[12pt]{minimal}
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\begin{document}$$n=8$$\end{document} teams of two) arm, respectively, whereby all teams, except for one dropout due to a technical failure in the intervention arm, went through an emergency simulation where they had to detect an emerging ST elevation myocardial infarction. The intervention group was endowed with a sonification-assisted equipment whereas the control group used standard visual-based ECG diagnosis only.

An adjusted multivariable regression yielded a statistically significant reduction for the intervention group of the delay time from starting a first ECG to the correct diagnosis by 163 seconds (\documentclass[12pt]{minimal}
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\begin{document}$$p = 0.002$$\end{document}) corresponding to \documentclass[12pt]{minimal}
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\begin{document}$$56\%$$\end{document} of the average delay time in the control group. A subgroup analysis within the intervention arm revealed a notable impact of the attitude toward sonification on delay time between the second ECG and diagnosis. Specifically, increasing disagreement with statement “I conceived the sound of the sonification as pleasant” counterintuitively reduced the delay, whereas an increasing disagreement with “sonification was helpful in making the diagnosis” increased the delay.

The sonification of ECG proved to be significantly superior as an accompanying diagnostic measure in emergency medical services in cases of suspected acute coronary syndrome in a simulated emergency scenario in terms of a proof-of-concept. The established dependence on individual attitudes towards sonification serves to further optimize sonification aesthetics and implementation with a focus on greater alertness and the reduction of stress-induced destraction or alarm fatigue.

The online version contains supplementary material available at 10.1186/s12873-025-01466-8.