Advances in Unobtrusive Monitoring of Sleep Apnea using Machine Learning

The PhD project focusses on the design of novel advanced signal processing algorithms and software starting from recordings of wearable sensors.
In particular, the research focusses on:

Identification of obstructive sleep apnea (OSA) or cardiovascular diseases (CVD) in a population of suspected OSA patients based on unobtrusive sensors.
Development of an artefact detection algorithm for novel unobtrusive sensors.
Development of an algorithmic framework to automatically synchronize distorted unobtrusive data with the reference data.Automated detection of sleep in OSA patients based on cardiac and respiratory data from unobtrusive sensors.

The research projects are conducted in strong collaboration with the University Hospital Leuven, industrial partners and other academic partners within Flanders and abroad.