Abstract
Electrocardiography (ECG) data are multidimensional temporal data with ubiquitous applications in the clinic. Conventionally, these data are presented visually. It is presently unclear to what degree data sonification (auditory display), can enable the detection of clinically relevant cardiac pathologies in ECG data. In this study, we introduce a method for polyphonic sonification of ECG data, whereby different ECG channels are simultaneously represented by sound of different pitch. We retrospectively applied this method to 12 samples from a publicly available ECG database. We and colleagues from our professional environment then analyzed these data in a blinded way. Based on these analyses, we found that the sonification technique can be intuitively understood after a short training session. On average, the correct classification rate for observers trained in cardiology was 78%, compared to 68% and 50% for observers not trained in cardiology or not trained in medicine at all, respectively. These values compare to an expected random guessing performance of 25%. Strikingly, 27% of all observers had a classification accuracy over 90%, indicating that sonification can be very successfully used by talented individuals. These findings can serve as a baseline for potential clinical applications of ECG sonification.
Highlights
Electrocardiography (ECG) data are multidimensional temporal data with ubiquitous applications in the clinic
Sonification has been applied to gene expression data[4], DNA methylation data[5], biological imaging data[6], electroencephalography (EEG) signals[7,8,9], electrocardiogram (ECG) signals[7,10] and combinations of biomedical signals[11]
After all observers had analyzed the data, we assessed whether sonified ECG signals could be used to distinguish clinically relevant cardiac pathologies
Summary
Electrocardiography (ECG) data are multidimensional temporal data with ubiquitous applications in the clinic. We introduce a method for polyphonic sonification of ECG data, whereby different ECG channels are simultaneously represented by sound of different pitch We retrospectively applied this method to 12 samples from a publicly available ECG database. Previous studies have proposed techniques for heart rate sonification[12] and ECG sonification[10,11], no study has evaluated in how far these techniques are suited for clinical application of ECG analysis To investigate this questions, we first designed a parameter-mapping sonification[13] method that applies time-variant oscillators to convert the multi-channel ECG datasets into a polyphonic sound. We first designed a parameter-mapping sonification[13] method that applies time-variant oscillators to convert the multi-channel ECG datasets into a polyphonic sound We applied this method to samples from a publicly available database[14]. We evaluated the diagnostic accuracy of common cardiac pathologies based on sonified ECG signals
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