Anomaly detection in elderly daily behavior in ambient sensing environments

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Edible robots and robotic food — edible systems that perceive, process and act upon stimulation — could open a new range of opportunities in health care, environmental management and the promotion of healthier eating habits. For example, they could enable ...

Background: Evaluating the impact of health systems on premature mortality across different countries is a very challenging task, as it is hardly possible to disentangle it from the influence of contextual factors such as cultural differences. In this resp ...

Dysregulations in cholesterol metabolism are associated with neurodegenerative and vascular pathologies, and dementia. Diet-derived plant sterols (phytosterols) have cholesterol-lowering, anti-inflammatory, and antioxidant properties and may interfere with ...

Rural mobility in Africa is an under-researched issue. Rural communities have often suffered from reduced mobility that has hampered their access to essential services and facilities such as education, health care, food, and clean water. In many rural comm ...

One of the most classical results in high-dimensional learning theory provides a closed-form expression for the generalisation error of binary classification with a single-layer teacher-student perceptron on i.i.d. Gaussian inputs. Both Bayes-optimal (BO) ...

This thesis focuses on two selected learning problems: 1) statistical inference on graphs models, and, 2) gradient descent on neural networks, with the common objective of defining and analysing the measures that characterize the fundamental limits. In th ...

Higher-order asymptotics provide accurate approximations for use in parametric statistical modelling. In this thesis, we investigate using higher-order approximations in two-specific settings, with a particular emphasis on the tangent exponential model. ...

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 ...

Measuring bathymetry has always been a major scientific and technological challenge. In this work, we used a deep learning technique for inferring bathymetry from the depth-averaged velocity field. The training of the neural network is based on 5742 labora ...

Mood inference with mobile sensing data has been studied in ubicomp literature over the last decade. This inference enables context-aware and personalized user experiences in general mobile apps and valuable feedback and interventions in mobile health apps ...

High comorbidity rates, especially mental-physical comorbidity, constitute an increasing health care burden, with women and men being differentially affected. To gain an overview of comorbidity rates stratified by sex across a range of different conditions ...

Statistical models for extreme values are generally derived from non-degenerate probabilistic limits that can be used to approximate the distribution of events that exceed a selected high threshold. If convergence to the limit distribution is slow, then th ...

A fit-for-purpose structural and statistical model is the first major requirement in population pharmacometric model development. In this manuscript we discuss how this complex and computationally intensive task could benefit from supervised machine learni ...

This thesis focuses on two kinds of statistical inference problems in signal processing and data science. The first problem is the estimation of a structured informative tensor from the observation of a noisy tensor in which it is buried. The structure com ...

Introduction:Population aging is increasing the needs and costs of healthcare. Both frailty and the chronic diseases affecting older people reduce their ability to live independently. However, most older people prefer to age in their own homes. New develop ...

Introduction Pituitary adenomas (PA) are common intracranial tumors. In the context of the aging of the population, the question is whether postsurgical outcomes are comparable to the younger ones. The primary objective of the present study was to review p ...

Adopting healthy behaviors can prevent the onset of many adverse health conditions. However, behavior changes are difficult to make, and often, people who like to improve their behaviors do not know how to do that. Personalizable intervention systems could ...

Understanding and predicting how people change their behavior after an intervention from time series data is an important task for health recommender systems. This task is especially challenging when the time series data is frequently sampled. In this pape ...

Uncertainty presents a problem for both human and machine decision-making. While utility maximization has traditionally been viewed as the motive force behind choice behavior, it has been theorized that uncertainty minimization may supersede reward motivat ...

In most studies of dam's displacement prediction based on monitoring data, emphasis was given on improving the prediction accuracy, while the model stability was merely considered. This study proposed a numerical-statistical combined model which aims to im ...

Anomaly detection in elderly daily behavior in ambient sensing environments

Chattez avec Graph Search

Towards edible robots and robotic food

Different health systems-Different mortality outcomes? Regional disparities in avoidable mortality across German-speaking Europe, 1992-2019

Plant sterols and cholesterol metabolism are associated with five-year cognitive decline in the elderly population

Impact of Topography on Rural Cycling Patterns: Case Study of Bugesera District, Rwanda

Learning curves for the multi-class teacher-student perceptron

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

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

Bed Topography Inference from Velocity Field Using Deep Learning

Generalization and Personalization of Mobile Sensing-Based Mood Inference Models: An Analysis of College Students in Eight Countries

Sex Differences in Comorbidity Combinations in the Swedish Population

Sub‐asymptotic motivation for new conditional multivariate extreme models

Population pharmacokinetic model selection assisted by machine learning

Statistical limits of high-dimensional inference problems

Evaluation of 1-Year in-Home Monitoring Technology by Home-Dwelling Older Adults, Family Caregivers, and Nurses

Transsphenoidal resection for pituitary adenoma in elderly versus younger patients: a systematic review and meta-analysis

Personalizable intervention systems to promote healthy behavior change

Recommender System for Responsive Engagement of Senior Adults in Daily Activities

Information Theoretic Characterization of Uncertainty Distinguishes Surprise From Accuracy Signals in the Brain

Improve the Model Stability of Dam's Displacement Prediction Using a Numerical-Statistical Combined Model