The field of cardiac electrophysiology tries to abstract, describe and finally model the electrical characteristics of a heartbeat. With recent advances in cardiac electrophysiology, models have become more powerful and descriptive as ever. However, to advance to the field of inverse electrophysiological modeling, i.e. creating models from electrical measurements such as the ECG, the less investigated field of smoothness of the simulated ECGs w.r.t. model parameters need to be further explored. The present paper discusses smoothness in terms of the whole pipeline which describes how from physiological parameters, we arrive at the simulated ECG. Employing such a pipeline, we create a test-bench of a simplified idealized left ventricle model and demonstrate the most important factors for efficient inverse modeling through smooth cost functionals. Such knowledge will be important for designing and creating inverse models in future optimization and machine learning methods. Copyright (C) 2022 The Authors.

Smoothness and continuity of cost functionals for ECG mismatch computation / Grandits, Thomas; Pezzuto, Simone; Plank, Gernot. - In: IFAC PAPERSONLINE. - ISSN 2405-8971. - 55:20(2022), pp. 181-186. [10.1016/j.ifacol.2022.09.092]

Smoothness and continuity of cost functionals for ECG mismatch computation

Pezzuto, Simone;
2022-01-01

Abstract

The field of cardiac electrophysiology tries to abstract, describe and finally model the electrical characteristics of a heartbeat. With recent advances in cardiac electrophysiology, models have become more powerful and descriptive as ever. However, to advance to the field of inverse electrophysiological modeling, i.e. creating models from electrical measurements such as the ECG, the less investigated field of smoothness of the simulated ECGs w.r.t. model parameters need to be further explored. The present paper discusses smoothness in terms of the whole pipeline which describes how from physiological parameters, we arrive at the simulated ECG. Employing such a pipeline, we create a test-bench of a simplified idealized left ventricle model and demonstrate the most important factors for efficient inverse modeling through smooth cost functionals. Such knowledge will be important for designing and creating inverse models in future optimization and machine learning methods. Copyright (C) 2022 The Authors.
2022
20
Grandits, Thomas; Pezzuto, Simone; Plank, Gernot
Smoothness and continuity of cost functionals for ECG mismatch computation / Grandits, Thomas; Pezzuto, Simone; Plank, Gernot. - In: IFAC PAPERSONLINE. - ISSN 2405-8971. - 55:20(2022), pp. 181-186. [10.1016/j.ifacol.2022.09.092]
File in questo prodotto:
File Dimensione Formato  
mathmod22_smooth_final.pdf

accesso aperto

Tipologia: Post-print referato (Refereed author’s manuscript)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 807.52 kB
Formato Adobe PDF
807.52 kB Adobe PDF Visualizza/Apri
1-s2.0-S2405896322012800-main.pdf

accesso aperto

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Creative commons
Dimensione 1.88 MB
Formato Adobe PDF
1.88 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/360218
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
  • OpenAlex ND
social impact