Music-Inspired MK545Pat for AF/PAF/Non-AF Classification Using ECG Signals

Gulensoy I. E., Tuncer I., Kivrak T., GÖKTAŞ Ö. F., Baygin M., Barua P. D., ...Daha Fazla

Bioengineering, cilt.13, sa.9, 2026 (SCI-Expanded, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 13 Sayı: 9
  • Basım Tarihi: 2026
  • Doi Numarası: 10.3390/bioengineering13091016
  • Dergi Adı: Bioengineering
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS, INSPEC, Directory of Open Access Journals, Academic Search Ultimate (EBSCO), Natural Science Collection (ProQuest), Biological Science Database (ProQuest), Materials Science & Engineering Collection (ProQuest), Technology Collection (ProQuest)
  • Anahtar Kelimeler: ablation, atrial fibrillation, deterministic feature engineering, ECG, music-inspired pattern, paroxysmal atrial fibrillation, patient-wise LOSO, segment-level evaluation
  • Ankara Yıldırım Beyazıt Üniversitesi Adresli: Evet

Özet

Paroxysmal atrial fibrillation (PAF) may be missed on intermittent electrocardiographic (ECG) recordings. We evaluated MK545Pat, a deterministic one-dimensional descriptor derived from the first-appearance order of the notes in Mozart’s Piano Sonata K.545. The CPSC 2021 dataset contains 1436 records from 105 patients, from which 116,042 15 s segments were analyzed. Each segment produced 2304 histogram features from 2942 unit-stride 59-sample blocks. Segment-level 10-fold cross-validation achieved 97.49 ± 0.18% accuracy (range, 97.16–97.71%), and a separate 90:10 segment-level holdout achieved 97.49% accuracy and 95.85% macro-F1. A separate patient-wise leave-one-subject-out (LOSO) analysis held out all records and segments from one patient at a time. The unweighted mean of the 105 held-out patient-specific segment accuracies was 71.29% (median, 78.17%; SD, 24.22%; range, 0.00–96.00%). Pattern controls were lower for identity, reverse, and interleaved assignments, while a within-group permutation retained 97.49%, as predicted by the invariance analysis. The results support MK545Pat as a reproducible feature-engineering approach and show the expected performance gap between segment-level and cross-patient evaluation.