TY  - JOUR
AB  - 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. 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.
DA  - 2017
DO  - 10.1038/srep44549
KW  - Sonification
KW  - auditory displays
KW  - electrocardiography
KW  - Arrhythmias
KW  - Data processing
KW  - Diagnostic markers
KW  - Scientific data
LA  - eng
IS  - 1
PY  - 2017
SN  - 2045-2322
T2  - Scientific Reports
TI  - Polyphonic sonification of electrocardiography signals for diagnosis of cardiac pathologies
UR  - https://nbn-resolving.org/urn:nbn:de:0070-pub-29085822
Y2  - 2024-11-22T00:52:32
ER  -