Context-aware health monitoring
The goal of this project is to gain more insight into the context, profile and lifestyle of people in order to identify triggers and behaviors linked to stress, depression and migraines. Identifying these triggers allows the people to make adaptations to their lifestyle to improve their health.
We use machine learning algorithm to assess the activities (e.g. sedentary, walking, running, lying, commuting), sleep (e.g. duration, quality) and emotional state of the user (e.g. stress) based on physiological collected data through wearables, i.e. the imec Chillband+ and Empatica E4.
These projects are a collaboration between UZ Ghent, IDLab Ghent University-imec, and imec-WHS.
EOS special issue on health and technology with mBrain contribution from PreDiCT
The Eos special has three parts. The first is about prevention. Thanks to sensors, digital doubles that collect all our medical data and personalized medicines, we can detect and prevent more diseases than ever before. Part two focuses on therapy. New AI models allow doctors to design more efficient treatments, tailored to the patient. The final part focuses on care and how robots can lend a mechanical hand, and investigates the most pressing question of the moment: how can we overcome infectious diseases?
One of the contributions within this EOS special issue covers the mBrain project and focuses on our research on migraine management using wearables.