Publications associées à The "systolic volume balance" method for the noninvasive estimation of cardiac output based on pressure wave analysis

Novel theory and potential applications of central diastolic pressure decay time constant

Nikolaos Stergiopoulos, Patrick Segers, Vasiliki Bikia, Georgios Rovas, Sokratis Anagnostopoulos

Central aortic diastolic pressure decay time constant ( ) is according to the two-element Windkessel model equal to the product of total peripheral resistance (R) times total arterial compliance (C ). As such, it is related to arterial stiffness, which has ...

2024

The role of computational methods in cardiovascular medicine: a narrative review

Alfio Quarteroni, Luca Dede', Christian Vergara, Stefano Pagani

Background and Objective: Computational models of the cardiovascular system allow for a detailed and quantitative investigation of both physiological and pathological conditions, thanks to their ability to combine clinical-possibly patient-specific-data wi ...

Ame Publishing Company2024

Implementation of an epicardial implantable MEMS sensor for continuous and real-time postoperative assessment of left ventricular activity in adult minipigs over a short- and long-term period

Silvestro Micera

The sensing of left ventricular (LV) activity is fundamental in the diagnosis and monitoring of cardiovascular health in high-risk patients after cardiac surgery to achieve better short- and long-term outcome. Conventional approaches rely on noninvasive me ...

Aip Publishing2024

Whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations

Alfio Quarteroni, Luca Dede', Francesco Regazzoni

Cardiac digital twins provide a physics and physiology informed framework to deliver personalized medicine. However, high-fidelity multi-scale cardiac models remain a barrier to adoption due to their extensive computational costs. Artificial Intelligence-b ...

Nature Portfolio2024

Partial discharge localization in power transformer tanks using machine learning methods

Farhad Rachidi-Haeri, Marcos Rubinstein, Hamidreza Karami

This paper presents a comparison of machine learning (ML) methods used for three-dimensional localization of partial discharges (PD) in a power transformer tank. The study examines ML and deep learning (DL) methods, ranging from support vector machines (SV ...

Nature Publishing Group2024

Apparatus for non-invasively computing cardio-vasculature parameters using morphology of uncalibrated pressure wave signal

Nikolaos Stergiopoulos, Vasiliki Bikia, Georgios Rovas

Systems and apparatus are provided for using a non-invasively monitored uncalibrated pressure signal from a patient to compute cardiac output and other cardio-vascular parameters, thereby providing safe, effective, reliable and low cost monitoring of patie ...

2024

Spectral Estimators for High-Dimensional Matrix Inference

Farzad Pourkamali

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

EPFL2024

Intermediate complexity atmospheric modeling in complex terrain: is it right?

Michael Lehning, Dylan Stewart Reynolds, Michael Haugeneder

Dynamic downscaling of atmospheric forcing data to the hectometer resolution has shown increases in accuracy for landsurface models, but at great computational cost. Here we present a validation of a novel intermediate complexity atmospheric model, HICAR, ...

Frontiers Media Sa2024

Health Prediction for Lithium-Ion Batteries Under Unseen Working Conditions

Florent Evariste Forest, Yunhong Che

Battery health prediction is significant while challenging for intelligent battery management. This article proposes a general framework for both short-term and long-term predictions of battery health under unseen dynamic loading and temperature conditions ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Fast-Response Variable-Stiffness Magnetic Catheters for Minimally Invasive Surgery

Dario Floreano, Jun Shintake, Yi Sun, Yegor Piskarev, Matteo Righi

In minimally invasive surgery, such as cardiac ablation, magnetically steered catheters made of variable-stiffness materials can enable higher dexterity and higher force application to human tissue. However, the long transition time between soft and rigid ...

2024

The hindbrain and cortico-reticular pathway in adolescent idiopathic scoliosis

Bénédicte Marie Maréchal

AIM: To characterise the corticoreticular pathway (CRP) in a case -control cohort of adolescent idiopathic scoliosis (AIS) patients using high -resolution slice -accelerated readoutsegmented echo -planar diffusion tensor imaging (DTI) to enhance the discri ...

W B Saunders Co Ltd2024

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Pakshal Narendra Bohra

In inverse problems, the task is to reconstruct an unknown signal from its possibly noise-corrupted measurements. Penalized-likelihood-based estimation and Bayesian estimation are two powerful statistical paradigms for the resolution of such problems. They ...

EPFL2024

Anisotropic Adaptive Finite Elements for a p-Laplacian Problem

Marco Picasso, Paride Passelli

The p-Laplacian problem -del & sdot; ((mu + |del u|(p-2))del u) = f is considered, where mu is a given positive number. An anisotropic a posteriori residual-based error estimator is presented. The error estimator is shown to be equivalent, up to higher ord ...

Walter De Gruyter Gmbh2024

Compliance-matching vascular grafts with personalization potential

Georgios Rovas

Aortic diseases are characterized by dire prognosis and inadequate diagnosis, owing to their insidious yet lethal nature. Aortopathies, namely aortic aneurysms and dissections, along with certain congenital diseases, might necessitate surgical replacement ...

EPFL2023

The Impact of Left Ventricular Performance and Afterload on the Evaluation of Aortic Valve Stenosis: A 1D Mathematical Modeling Approach

Nikolaos Stergiopoulos

The transaortic valvular pressure gradient (TPG) plays a central role in decision-making for patients suffering from severe aortic stenosis. However, the flow-dependence nature of the TPG makes the diagnosis of aortic stenosis challenging since the markers ...

MDPI2023

Cardiac output estimated from an uncalibrated radial blood pressure waveform: validation in an in-silico-generated population

Nikolaos Stergiopoulos, Vasiliki Bikia, Georgios Rovas

Background: Cardiac output is essential for patient management in critically ill patients. The state-of-the-art for cardiac output monitoring bears limitations that pertain to the invasive nature of the method, high costs, and associated complications. Hen ...

FRONTIERS MEDIA SA2023

Modulation of Pulsatile Left Ventricular Afterload by Renal Denervation in Heart Failure With Preserved Ejection Fraction

Nikolaos Stergiopoulos, Stamatia Zoi Pagoulatou

Background:Arterial stiffening contributes to hemodynamic derangements in heart failure with preserved ejection fraction (HFpEF). We sought to investigate the impact of renal denervation on pulsatile left ventricular loading in patients with HFpEF and hype ...

Lippincott Williams & Wilkins2023

Hemodynamic effects of a dielectric elastomer augmented aorta on aortic wave intensity: An in-vivo study

Yves Perriard, Yoan René Cyrille Civet, Silje Ekroll Jahren, Thomas Guillaume Martinez, Francesco Clavica, Armando Matthieu Walter, Lorenzo Ferrari

Dielectric elastomer actuator augmented aorta (DEA) represents a novel approach with high potential for assisting a failing heart. The soft tubular device replaces a section of the aorta and increases its diameter when activated. The hemodynamic interactio ...

2023

On the similarity between aortic and carotid pressure diastolic decay: a mathematical modelling study

Nikolaos Stergiopoulos, Vasiliki Bikia, Georgios Rovas, Sokratis Anagnostopoulos

Aortic diastolic pressure decay (DPD) has been shown to have considerable pathophysiological relevance in the assessment of vascular health, as it is significantly affected by arterial stiffening. Nonetheless, the aortic pressure waveform is rarely availab ...

Nature Portfolio2023

Efficient approximation of cardiac mechanics through reduced-order modeling with deep learning-based operator approximation

Alfio Quarteroni, Andrea Manzoni

Reducing the computational time required by high-fidelity, full-order models (FOMs) for the solution of problems in cardiac mechanics is crucial to allow the translation of patient-specific simulations into clinical practice. Indeed, while FOMs, such as th ...

Wiley2023