Left Ventricular Pressure Estimation Using Machine Learning-Based Heart Sound Classification

Autor: Philip Westphal, Hongxing Luo, Mehrdad Shahmohammadi, Luuk I. B. Heckman, Marion Kuiper, Frits W. Prinzen, Tammo Delhaas, Richard N. Cornelussen

Publikováno v: Frontiers in Cardiovascular Medicine, Vol 9 (2022)

ObjectiveA method to estimate absolute left ventricular (LV) pressure and its maximum rate of rise (LV dP/dtmax) from epicardial accelerometer data and machine learning is proposed.MethodsFive acute experiments were performed on pigs. Custom-made acc

Externí odkaz: https://doaj.org/article/96e3a4c043804ebebd483ad5e1e6f5e3

Heart sound-derived systolic time intervals for atrioventricular delay optimization in cardiac resynchronization therapy

Autor: Hongxing, Luo, Philip, Westphal, Mehrdad, Shahmohammadi, Luuk I B, Heckman, Marion, Kuiper, Richard N, Cornelussen, Tammo, Delhaas, Frits W, Prinzen

Publikováno v: Heart Rhythm, 20(4), 572-579. Elsevier Science

Background: Phonocardiography (PCG) can be used to determine systolic time intervals (STIs) from ventricular pacing spike to the first heart sound (VS1) and from the first to the second heart sound (S1S2). Objective: The purpose of this study was to

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1a490dd3f4d8a18a8d8c5e8ddc123dcf
https://doi.org/10.1016/j.hrthm.2022.12.031

CI-452767-3 MACHINE LEARNING-POWERED, DEVICE-EMBEDDED HEART SOUND MEASUREMENT CAN OPTIMIZE AV DELAY IN CRT PATIENTS

Autor: Frits W. Prinzen, Philip Westphal, Hongxing Luo, Mehrdad Shahmohammadi, Tammo Delhaas, Richard N. Cornelussen

Publikováno v: Heart Rhythm. 20:S26

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::adfdab5773fed20c44e43d43f53b1873
https://doi.org/10.1016/j.hrthm.2023.03.251

The 'Digital Twin' to enable the vision of precision cardiology

Autor: Pras Pathmanathan, Liesbet Geris, Yingjing Feng, Francesca Margara, Andrew Gilbert, Espen W. Remme, Alfonso Bueno-Orovio, Joao Filipe Fernandes, Mark Potse, Marta Sitges, Blanca Rodriguez, Viatcheslav Gurev, Tammo Delhaas, Tina M. Morrison, Manuel Villegas Martinez, Pablo Lamata, Ali Wajdan, Ada Doltra, Filip Loncaric, Hassaan A. Bukhari, Richard Cornelussen, Paul Leeson, Paolo DiAchille, Frits W. Prinzen, Peter Mortier, Manuel Mayr, Hongxing Luo, Edward J. Vigmond, Mehrdad Shamohammdi, Esther Pueyo, Kristin McLeod, Philip Westphal, Vicente Grau, Jorge Corral-Acero, Ernesto Zacur, Steven A. Niederer, Mariana Sousa Santos, Maciej Marciniak, Cristobal Rodero

Publikováno v: European Heart Journal Supplements
European Heart Journal Supplements, Oxford University Press (OUP), In press, pp.1-11. ⟨10.1093/eurheartj/ehaa159⟩
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European Heart Journal, Oxford University Press (OUP): Policy B, 2020, 41 (48), pp.4556-4564. ⟨10.1093/eurheartj/ehaa159⟩
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European Heart Journal
European Heart Journal, 2020, 41 (48), pp.4556-4564. ⟨10.1093/eurheartj/ehaa159⟩
Zaguán. Repositorio Digital de la Universidad de Zaragoza
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Providing therapies tailored to each patient is the vision of precision medicine, enabled by the increasing ability to capture extensive data about individual patients. In this position paper, we argue that the second enabling pillar towards this vis

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c97ae7c451477bf2bd40d8067a5c65e
https://hal.inria.fr/hal-02947289