Publications related to Predicting Heart Activity from Speech using Data-driven and Knowledge-based features

Related publications (8)

Testing an inverse modeling approach with gradient boosting regression for stroke volume estimation using patient thermodilution data

Nikolaos Stergiopoulos, Vasiliki Bikia, Georgios Rovas

Stroke volume (SV) is a major indicator of cardiovascular function, providing essential information about heart performance and blood flow adequacy. Accurate SV measurement is particularly important for assessing patients with heart failure, managing patie ...

FRONTIERS MEDIA SA2025

On the Utility of Speech and Audio Foundation Models for Marmoset Call Analysis

Mathew Magimai Doss, Eklavya Sarkar

Marmoset monkeys encode vital information in their calls and serve as a surrogate model for neuro-biologists to understand the evolutionary origins of human vocal communication. Traditionally analyzed with signal processing-based features, recent approache ...

2024

An Automatic Speaker Clustering Pipeline for the Air Traffic Communication Domain

Juan Pablo Zuluaga Gomez

In air traffic management (ATM), voice communications are critical for ensuring the safe and efficient operation of aircraft. The pertinent voice communications-air traffic controller (ATCo) and pilot-are usually transmitted in a single channel, which pose ...

2023

A comprehensive mathematical model for cardiac perfusion

Alfio Quarteroni, Francesco Regazzoni, Christian Vergara

The aim of this paper is to introduce a new mathematical model that simulates myocardial blood perfusion that accounts for multiscale and multiphysics features. Our model incorporates cardiac electrophysiology, active and passive mechanics, hemodynamics, v ...

Nature Portfolio2023

On Breathing Pattern Information in Synthetic Speech

Mathew Magimai Doss, Zohreh Mostaani

The respiratory system is an integral part of human speech production. As a consequence, there is a close relation between respiration and speech signal, and the produced speech signal carries breathing pattern related information. Speech can also be gener ...

ISCA-INT SPEECH COMMUNICATION ASSOC2022

PDE-Aware Deep Learning for Inverse Problems in Cardiac Electrophysiology

Alfio Quarteroni, Simone Deparis, Stefano Pagani, Riccardo Tenderini

In this work, we present a PDE-aware deep learning model for the numerical solution to the inverse problem of electrocardiography. The model both leverages data availability and exploits the knowledge of a physically based mathematical model, expressed by ...

2022

Interbeat Interval Detection from Synthetic Photoplethysmography Signals

Clémentine Léa Aguet, Loïc François Andrée Jeanningros

With the increased presence of wearables, photoplethysmography (PPG) is a promising alternative to electrocardiography (ECG) for the monitoring of physiological parameters related to cardiovascular diseases. However, the evaluation of PPG-based methods is ...

IEEE2021

Deep Learning Approaches for Auditory Perception in Robotics

Weipeng He

Auditory perception is an essential part of a robotic system in Human-Robot Interaction (HRI), and creating an artificial auditory perception system that is on par with human has been a long-standing goal for researchers. In fact, this is a challenging res ...

EPFL2021