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More and more people suffer, nowadays, from a too high cholesterol level in the blood. These cholesterol molecules attach to the arterial walls leading to obstructions in the arteries. This effect causes all kinds of problems, such as heart problems, thromboses,… To detect these thickenings in the artery walls, the Vascular Transit Time (VTT, the time for an arterial pressure wave to cover a predefined distance) is measured by means of ultra-sound Doppler. However, this technique is very expensive and needs an experienced laboratory technician.
To overcome these shortcomings a miniaturized and integrated photonic sensor consisting of an array of sources and photodiodes that can be fabricated at low cost is needed to fully exploit the potential advantages of sensors for biomedical applications . The sensor will be applicable by layman users.
This master thesis is a joint effort of 2 research groups within the Faculty of Engineering Sciences at VUB, the Medical Measurements and Signal Analysis Team (M2ESA/ELEC) and the Brussels Photonics Team (TONA). The research group M2ESA combines powerful signal analysis tools and modeling techniques to medical applications such as calibrating blood pressure meters, non-invasive glucose sensors, functional Magnetic Resonance Imaging. A large expertise has been build up in signal reconstruction and analysis tools for diagnostics.
At TONA we have fabricated prototypes of miniaturized photonic sensors consisting of LEDs, photodiodes and integrated plastic optics and we have used them successfully in proof-of-concept demonstration set-ups. Up to now their measurement principle relies in most cases on laser-induced fluorescence and absorbance analysis. In this thesis you can go a step further and combine the expertise of both research groups to develop a blood flow speed sensor.
Illustration 1 : Commercial oxygen blood sensor
The goal of your thesis is in a first step to build a proof-of-concept demonstrator by selecting the most appropriate source, detector and optics and secondly to apply the signal analysis tools to discriminate noise and the actual blood flow speed. This signal analysis allows optimizing the speed sensor to obtain the most accurate estimate of the blood flow speed. This sensor will form a significant extension of a classical blood oxygen sensor and may also open a potential path to a new measurement technique for blood pressure meters.
This multidisciplinary master thesis, consisting of both signal analysis and experimental work, offers you challenging research opportunities within the framework of on-going research projects.
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