Signal Processing Approaches for Cardio-Respiratory Biosignals with an Emphasis on Mobile Health Applications

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

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 ...

In a context of escalating public health challenges, including the rise of chronic diseases, the impact of climate change, and the COVID-19 pandemic, certain populations bear a disproportionate burden. As a result, there is an urgent need to develop public ...

Buildings are designed to respond to functional and regulatory needs, providing comfortable conditions to occupants, offering satisfactory environmental settings, minimising health risks, and enhancing individual and collective quality of life. Although th ...

Robotics is entering our daily lives. The discipline is increasingly crucial in fields such as agriculture, medicine, and rescue operations, impacting our food, health, and planet. At the same time, it is becoming evident that robotic research must embrace ...

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 ...

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 ...

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

Sedentary lifestyle is currently considered a global pandemic, associated with major health problems such as cardiovascular disease and premature death. Regular physical activity (PA) is one way to address this problem, as it brings a variety of health ben ...

Atrial fibrillation (AF) is the most common cardiac arrhythmia; it will affect one in four adults worldwide in their lifetime. AF has serious consequences, including drastically increased risk of stroke. Catheter ablation surgery is an established treatmen ...

Self-tracking technologies open new doors to previously unimaginable scenarios. The diagnosis of diseases years in advance, or supporting the health of astronauts on missions to Mars are just some of many example applications. During the COVID-19 pandemic, ...

As the world’s population grows in cities, urban dwellers spend a large amount of time inside their home, making housing health ever more important. Critical for residents’ health, the interactions between indoor residential environments and outdoor enviro ...

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 ...

Acute leukemia has a high mortality rate of approximately 50%, and current methods are not effective in predicting disease progression and relapse. To improve our understanding of hematopoiesis and develop new markers for predicting disease relapse in dead ...

The integration of technology in the medical field has greatly improved accuracy in diagnoses, thus leading to more effective treatments. Wearable and implantable medical devices offer great potential for remote patient monitoring, particularly for heart f ...

Background: The impact of acute unilateral injury on spontaneous electrical activity in both vagus nerves at the heart level is poorly understood. We investigated the immediate neuroelectrical response after right or left cardiac vagal nerve transection (V ...

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 ...

Stimulated by the COVID-19 outbreak, the global healthcare industry better acknowledges the necessity of innovating novel methods for remote healthcare monitoring and treating patients outside clinics. Here we report the development of two different types ...

Background:Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive p ...

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 ...

The Bio Image and Signal Processing (BISP) Technical Committee (TC) of the IEEE Signal Processing Society (SPS) promotes activities within the broad technical field of biomedical image and signal processing. Areas of interest include medical and biological ...

Signal Processing Approaches for Cardio-Respiratory Biosignals with an Emphasis on Mobile Health Applications

Chattez avec Graph Search

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

The role of spatial epidemiology to support public health policies : case studies applied to health promotion, noncommunicable and infectious diseases in the canton of Vaud, Switzerland

What is NExT? A new conceptual model for comfort, satisfaction, health, and well-being in buildings

Soft Robotics: A Route to Equality, Diversity, and Inclusivity in Robotics

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

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

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

Real world multimodal assessment of physical behavior change in health and disease

Finding information-rich electrocardiographic biomarkers to characterize atrial fibrillation

Designing self-tracking experiences: A qualitative study of the perceptions of barriers and facilitators to adopting digital health technology for automatic urine analysis at home

Housing, street and health: a new systemic research framework

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

Novel quantitative bioengineered tools to track human bone marrow niche cellular constituents in health and disease

Integrated Electronics for Deep Implants to Remotely Monitor Hemodynamics

Left cardiac vagotomy rapidly reduces contralateral cardiac vagal electrical activity in anesthetized Gottingen minipigs

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

Single-arm diagnostic electrocardiography with printed graphene on wearable textiles

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

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

From Nano to Macro An overview of the IEEE Bio Image and Signal Processing Technical Committee