PhD Projects

Human milk is far more than a static source of nutrition. The nutritional content of the milk is dynamic and tailored to fit the state of the infant needs, with varying concentrations of macro- and micro nutritional compounds.

This project aims to design behaviour change interventions to promote behaviour paths that reduce the risk of infection and contagion or to add barriers to the performance of infection and contagion risk-related behaviours in the context of nursing homes.

This project uses VR, AR, and XR to create interactive human-machine interfaces for home-based stroke rehabilitation. It sets out to investigate the potential of digital twins and immersive technologies for sustained behaviour change over time.

Body Age calculation has become a frequently used health tool. This project investigates the use of Body Age technologies and explores its potential as a reliable health technology in the prevention of lifestyle related diseases.

Healthcare Design for Collaborative Care aims to investigate how technology and services in collaborative healthcare can be designed in such a way that digital and human-centered treatment models can ensure better and more effective treatment of the chronic patient group.

The research project FitMum will generate evidence about how to implement physical activity in pregnant women’s everyday life by testing the efficacy of two very different exercise programs on physical activity levels during pregnancy.

This PhD project will investigate 1) the validity of commercial PA tracker by comparing their data with doubly labelled water (DLW) and pregnancy physical activity questionnaire PPAQ. 2) Will examine the Effects of FitMum PA intervention on sleep quantity and quality as determined by activity trackers. 3) Effects of FitMum RCT on PA level of mothers in one year after delivery.

In this PhD project, a novel miniaturized device - the InstaPatch - for instantaneous and quantitative monitoring of allergic reactions in the skin will be developed.

Among patients with chronic medical diseases, patients with exacerbation of chronic obstructive pulmonary disease (COPD) are among those with the poorest prognosis despite advances in medical therapy. This project explores the use of continuous monitoring of vital signs for early detection of critical deteriorations in patients with exacerbation of COPD.

There is an undeniable increase of behaviour related challenges in society rooted in poor choice of behaviour, and the inability of conventional approaches to tackle them.

This project uses new technology to determine whether increased listening effort is associated with cognitive function, and to investigate how to integrate this new tool at point-of-care in dementia and hearing care settings.

It has been shown that craniofacial features are predictive of OSA, and a diagnostic system based on craniofacial images would offer a cheap and efficient alternative to the PSG.

People with severe mental illness (SMI) die 10-20 years earlier than the general population. People with SMI have a higher prevalence of physical comorbidities than the general population.

Automatic analysis of sleep patterns has the potential to efficiently diagnose sleep disorders such as REM sleep behavior disorder, a precursor of Parkinson’s disease. Early and efficient diagnosis is therefore essential to identify patients at high risk of developing overt neurogenerative disease.