Automated Musical Rhythm Transcription of ECG RR Interval Time Series as a Tool for Representing Rhythm Variations and Annotation Anomalies in Arrhythmia Heartbeat Classifications - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2022

Automated Musical Rhythm Transcription of ECG RR Interval Time Series as a Tool for Representing Rhythm Variations and Annotation Anomalies in Arrhythmia Heartbeat Classifications

Résumé

We introduce a linear time algorithm for transcribing RR intervals into musical rhythms using approximate common divisors (ACDs). The technique maps ACDs to nodes on a graph, node transitions represent heart rate variations; a balance must be struck between rhythmic changes and heart rate variation. Possible transcriptions correspond to paths in the ACD graph. Given a set of weights, a shortest path algorithm finds the optimal transcription. The representation facilitates efficient pattern recognition and extraction. The transcription technique is applied to the Physionet Long Term Atrial Fibrillation Database to demonstrate how it shows the rhythmic variation within heartbeat subsequences having the same labels, and its utility in detecting potential labelling errors on its own and via a rhythm simplex. Further work may explore prospective applications to arrhythmia stratification.
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Dates et versions

hal-03779244 , version 1 (16-09-2022)

Identifiants

  • HAL Id : hal-03779244 , version 1

Citer

Gonzalo Romero-García, Paul Lascabettes, Elaine Chew. Automated Musical Rhythm Transcription of ECG RR Interval Time Series as a Tool for Representing Rhythm Variations and Annotation Anomalies in Arrhythmia Heartbeat Classifications. Computing in Cardiology, Sep 2022, Tampere, Finland. ⟨hal-03779244⟩
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