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

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Understanding behavior requires datasets that capture humans while carrying out complex tasks. The kitchen is an excellent environment for assessing human motor and cognitive function, as many complex actions are naturally exhibited in kitchens from choppi ...

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 ...

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 ...

Monitoring the health of complex industrial assets is crucial for safe and efficient operations. Health indicators that provide quantitative real-time insights into the health status of industrial assets over time serve as valuable tools for, e.g., fault d ...

Motivation is a multifaceted phenomenon that we explore within the framework of decision-making. Through this cognitive process, actions are directed towards specific goals by performing a trade-off between the cost and benefit of an action. The dorsomedia ...

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 ...

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 ...

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

In this paper, we extend the dataset statistics, model benchmarks, and performance analysis for the recently published KABR dataset, an in situ dataset for ungulate behavior recognition using aerial footage from the Mpala Research Centre in Kenya. The data ...

Over the past two decades, protein S-acylation (often referred to as S-palmitoylation) has emerged as an important regulator of vital signalling pathways. S-Acylation is a reversible post-translational modification that involves the attachment of a fatty a ...

The technological advancements of the past decades have allowed transforming an increasing part of our daily actions and decisions into storable data, leading to a radical change in the scale and scope of available data in relation to virtually any object ...

Sweat secreted by the human eccrine sweat glands can provide valuable biomarker information during exercise. Real-time non-invasive biomarker recordings are therefore useful for evaluating the physiological conditions of an athlete such as their hydration ...

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 ...

Wearable biosensors and smartphone applications can measure physiological variables over multiple days in free-living conditions. We measure food and drink ingestion, glucose dynamics, physical activity, heart rate (HR), and heart rate variability (HRV) in ...

Background: The COVID-19 pandemic disrupted the delivery of diabetes care and worsened mental health among many patients with type 2 diabetes (T2D). This disruption puts patients with T2D at risk for poor diabetes outcomes, especially those who experience ...

An important initial step in fault detection for complex industrial systems is gaining an understanding of their health condition. Subsequently, continuous monitoring of this health condition becomes crucial to observe its evolution, track changes over tim ...

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, ...

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 ...

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

Chattez avec Graph Search

EPFL-Smart-Kitchen-30 Annotations and Poses

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

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

Learning Informative Health Indicators Through Unsupervised Contrastive Learning

Neurobiological and metabolic basis of motivation and effort-based decision-making - A human 1H-MRS, fMRI and machine learning study

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

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

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Deep dive into KABR: a dataset for understanding ungulate behavior from in-situ drone video

Mechanisms and functions of protein S-acylation

Discrete choice modeling in the era of big data

Multisensing wearables for real-time monitoring of sweat electrolyte biomarkers during exercise and analysis on their correlation with core body temperature

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

Uncovering personalized glucose responses and circadian rhythms from multiple wearable biosensors with Bayesian dynamical modeling

Technology-Enabled Collaborative Care for Concurrent Diabetes and Distress Management During the COVID-19 Pandemic: Protocol for a Mixed Methods Feasibility Study

A Comparison of Residual-based Methods on Fault Detection

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

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