Spatial-Temporal Mercer Kernel for Premature Ventricular Complex Estimation in Electrocardiographic Imaging
52nd International Computing in Cardiology, CinC 2025, Sao-Paulo, Brezilya, 14 - 17 Eylül 2025, cilt.52, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Cilt numarası: 52
- Doi Numarası: 10.22489/cinc.2025.161
- Basıldığı Şehir: Sao-Paulo
- Basıldığı Ülke: Brezilya
- Orta Doğu Teknik Üniversitesi Adresli: Evet
Özet
Cardiovascular diseases are a leading cause of death globally, highlighting the need for accurate, noninvasive diagnostic tools. Electrocardiographic imaging (ECGI) has emerged as a promising technique for reconstructing epicardial potentials from body surface measurements, offering an alternative to invasive procedures. This work presents a novel spatio-temporal separable Mercer kernel framework for estimating premature ventricular complex (PVC) origins, aiming to enhance the precision of ECGI-based localization. We incorporate spatial-temporal correlations in the kernel and use ADAM optimization to model epicardial potential dynamics. The proposed approach is evaluated using real ECGI data, and its performance is compared to traditional methods, including the Tikhonov regularization. Results show that the Gaussian kernel achieves the lowest NSME (0.3439) and smallest localization error (12.55 mm), outperforming the Laplacian kernel (NSME = 0.3503; 23.99 mm) and Tikhonov (NSME = 0.5036; 36.48 mm). This study contributes to advancing ECGI as a reliable tool for guiding catheter ablation in PVC patients, improving clinical outcomes through previous localization.