Course description Digital health is a branch of digital medicine that integrates and leverages multisource and multimodal data for medical knowledge extraction and decision support across a wide range of preventive, diagnostic, and therapeutic applications. The course starts by introducing the basi...
Course description The course provides an overview on the design of wearable and implantable computing systems. The overview is structured in three parts: context recognition, electronic systems and sensors, and additive manufacturing methods. Pattern analysis and machine learning methods to process...
Background Nowadays the new digital modelling techniques can speed up the personalisation of wearables as well as the rapid prototyping. However, the personalisation might require very precise human body measurements which can be tedious if done manually. The project aims at implementing a convenien...
Background Web scraping methods can nowadays be very helpful to automatically collect data and build large-sized datasets which can be necessary when developing machine learning algorithms. The project aims at implementing a convenient algorithm for the automatic extraction and tagging of audio data...
Background Wearable technology often needs devices to be personalized in order to achieve comfort and usability requirements for a long-term, inconspicuous monitoring of the user health. We propose to implement an algorithm to speed up the customization and manufacturing of smart clothes. Aim The pr...
Background COVID-19 has forced the world into social distancing and self-isolation, and with the general goal of not saturating the healthcare system, establishing an adequate threshold for when to contact the doctor is difficult. Some people may be overreacting to any minor symptom, while other peo...
Background The field of knowledge discovery has focused on the extraction of rules created from the frequent association symbols. With the recent introduction of the Bayesian rule mining algorithms, the focus is shifting from measuring relevance based on rule frequency and moving towards the increas...
Background Particle models can be used to simulate population behaviour. Using the simulated behaviours, we can analyse the different components that affect spreads of infections. Our current experience with the pandemic has shown that different regions might have a different response to similar int...
