PhD project by Mads Olsen

Name: Mads Olsen
Project Title: Design of monitoring systems for chronic sleep/brain disorders
Group: Biomedical Signal Processing and AI
Supervisor: Helge B.D. Sørensen
Co-supervisor: Poul Jørgen Jennum

Project Description:
Chronic sleep disorders such as obstructive sleep apnea (OSA) is a significant health condition, which is time consuming and expensive to diagnose. This project aims to design and clinically validate a simple monitoring systems for chronic sleep disorders.


Chronic sleep disorders cause significant personal, familiar, health and societal consequences [1-3]. This is particularly true for obstructive sleep apnea (OSA) which affects more than 4% of the population [4]. Current diagnoses are based on submission primarily from the general practice when a suspicion of OSA is raised. The patients are submitted for further investigation with cardiorespiratory measures (CRM) or gold standard polysomnography (PSG), which includes measures of sleep pattern and cardio-respiratory measures [5]. The procedures are highly standardized but include diagnoses on hospital using advanced medical equipment. The recording is typically made in hospital settings (in-hospital or as ambulatory measures) but the patient need contacts with the hospital for the nocturnal stay or as home recording bringing the equipment to the hospital after the recording. The analysis is time consuming taking up to 4-5 hour analyze time for experienced technicians. Consequently, the procedure is expensive. A significant problem is that more than 50% of those submitted do not suffer from OSA. There is a need for methods for identification of patients in primary sector and/or in patients with high risk of OSA, and procedures which may screen for identification of candidates submitted for further management in hospital settings for increasing the number of positive diagnosed patients and reducing the number of patients with negative test.

Project objectives

The main objective for this research project is to design monitoring systems, for chronic sleep disorders capable of monitoring, analysis, and interpretation of abnormal events opening for ground breaking earlier and better disease treatment and prevention of serious worsening of chronic diseases and furthermore disease prevention. Intelligent multi-modal biomedical signal processing, signal interpretation, and machine learning algorithms will be designed, implemented, and clinical tested and validated using large scale clinical samples to achieve these goals.


Mads Olsen


Helge Bjarup Dissing Sørensen
Gruppeleder, Lektor MSK, Ph.D.
DTU Sundhedsteknologi
45 25 52 44