Are you inspired by signal processing and artificial intelligence for biomedical applications? This project is aimed at sleep apnea, one of the most prevalent sleep disorders. The goal is to develop new predictors of clinical relevance, severity and therapy outcome using a combination of signal processing and big data approaches.
Obstructive Sleep Apnea (OSA) is one of the most prevalent sleep disorders with a strong negative impact on quality of life, and increased risk of cardiovascular complications. Current screening and diagnosis of OSA is biased towards a specific group: middle-aged obese men with frequent snoring. However, there are many patients that do not fit this stereotype, and presentation of the disease can be highly variable. Current diagnostic outcomes often fail at linking symptom severity (e.g. sleepiness) to objective measures of sleep. This makes it difficult to predict future risk factors or selection of treatment. There is therefore a need for better screening, triaging and diagnosis tools that -besides identifying groups with clinically relevant sleep apnea- indicate which therapy will likely be accepted and effective in alleviating night- and day-time symptoms.
This project ultimately aims to develop improved screening, triaging and diagnosing tools for OSA, based on a) discovering clinically relevant OSA phenotypes based on big data from an existing large multimodal retrospective data base, and b) classification of patients into these new phenotypes using a combination of sensing strategies and clinical information.
The aim of this project is twofold:
This project will make use of existing patient data, including one or two-night clinical PSG recordings, multiple day/night recordings of wearable photoplethysmography, night-time seismocardiography, and questionnaires and sleep/wake diaries. When possible outcome variables such as success of treatment will be included in the analysis.
The candidate should have:
A PhD position in a vibrant and dynamic high-tech environment. You can perform research on a highly relevant topic that can influence the quality of life for many patients, with the potential to see and help your research results get implemented in clinical practice. Furthermore, we offer
This project will be embedded within the Eindhoven MedTech Innovation Center (e/MTIC). This is a public-private partnership that aims to create a fast track to high-tech-health innovations in the perinatal, cardiovascular and sleep fields. It combines an academic partner (TU Eindhoven) with an industrial partner (Philips Research) and 3 semi-academic hospitals: Maxima Medical Center, Catharina Hospital, and Kempenhaeghe. On a project-specific basis e/MTIC also involves other parties that can help reinforce these projects.
Do you recognize yourself in this profile and would you like to know more? Please contact
dr.ir. R. Vullings, r.vullings[at]tue.nl.
For information about terms of employment, click here or contact the HR department:
Please visit www.tue.nl/jobs to find out more about working at TU/e!
We invite you to submit a complete application by using the 'apply now'-button on this page.
The application should include a:
We look forward to your application and will screen it as soon as we have received it. Screening will continue until the position has been filled.