PICASSO project; Long-term, at home sleep monitoring; a multimodal approach for better diagnostic outcomes
Eindhoven University of Technology (TU/e) is one of Europe’s top technological universities, situated in the heart of one of Europe’s largest high-tech innovation ecosystems. Research at TU/e is characterized by a combination of academic excellence and a strong real-world impact. This impact is often obtained via close collaboration with high-tech industries and key clinical centers.
In the Healthcare field, TU/e is part of a large collaborative multidisciplinary research program called the Eindhoven MedTech Innovation Center (e/MTIC). e/MTIC focuses in part on improved diagnosis and treatment of sleep disorders, with the Kempenhaeghe Center for Sleep Medicine serving as the primary clinical partner. For this project we are looking for a PhD candidate who will be appointed at TU/e, but also embedded for a part of his/her time at Kempenhaeghe and Philips Research, both located in the direct vicinity of TU/e.
There remain a large number of undiagnosed people suffering from clinically relevant sleep disorders, resulting in a huge health and economic impact. Current diagnostic procedures for sleep disorders are too expensive and have too low specificity to allow population screening. Moreover, the current gold-standard of in-laboratory polysomnography is limited to 1 or 2 nights, failing to capture the night-to-night variability in the expression of sleep disorders. Diagnostic approaches also do not use the potential for long term assessment of subjective sleep complaints.
Recent developments in sensor and analysis technologies now enable simplified measurements of physiological characteristics at home during longer time periods. These include cardiorespiratory based methods for sleep staging, for example with wearable reflective photoplethysmography, ballistocardiographic measurements with bed sensors or body-mounted accelerometers, and simplified EEG setups using dry-electrodes which can be easily and reliably set up by the patient at home. Furthermore, app-technology makes it possible to easily log subjective sleep habits and complaints as well. In recent years, we have made important contributions to the development and initial validation of these technologies.
This now opens up the possibility to perform longitudinal measurements over several nights without negatively affecting the sleep quality of the user. We hypothesize that this will enable more precise diagnosis of sleep disorders, their subtypes and potential co-morbidities, with the objective to enable clinicians to make better treatment recommendations.
Key scientific aims of this PhD project are:
We are looking for candidates who:
For more information about the advertised position, please contact dr. Merel van Gilst, M.M.v.Gilst[at]tue.nl,More information on employment conditions can be found here: https://www.tue.nl/en/working-at-tue/ .
If interested, please use the 'apply now'-button at the top of this page. You should upload the following:
- a cover letter explaining your motivation and suitability for the position;
- a detailed Curriculum Vitae;
- a written scientific report in English (MSc thesis, traineeship report or scientific paper)
- copies of diplomas with course grades (transcripts).
You can upload only one document (maximum file size is 10 MB). You have to bundle the documents.