Thesis/Project Openings

Open Bachelor’s Theses

We are developing a learning game based on the Microsoft Kinect camera. Students use the Kinect to browse volumetric data and mark region of interests.

Tasks include:

  • Reimplement the OrganChallenge framework in .NET
  • Implement additional games
  • Evaluate usability and learning effectiveness


KONTAKT
Stephan Jonas
sjonas@mi.rwth-aachen.de

The IMCAR at the Uniklinik RWTH Aachen is developing a novel microscopy modality for imaging muscle traction. In this thesis, the muscle traction captured on the microscopy images should be analyzed and quantified in a meaningful way (i.e., flow charts, etc).


KONTAKT
Stephan Jonas
sjonas@mi.rwth-aachen.de

In this project, data recorded from a smart shirt will be analyzed on a connected smartphone regarding stress, fatigue and posture. The shirt records basic vital parameters through inexpensive sensors (audio, acceleration)
The tasks include:

  • Processing of the raw input signal to physiological parameters (heart rate, posture, motion)
  • Optimization of the bluetooth transmission protocol
  • Live-evaluation of basic parameters regarding possible overload (posture, stress, fatigue) using existing methods (heart rate variability, …)

For details visit http://mhealth.imib.rwth-aachen.de/hobs/


KONTAKT
Stephan Jonas
sjonas@mi.rwth-aachen.de

Open Master’s Theses

Open Student Projects

Virtual reality (VR) is a topic of high interest for data visualization in clinical research. However, sometimes it might be necessary to control machinery or devices while being immersed in VR. Thus, the aim of this project is the development of a “windows to the real world”, by embedding camera live-feeds into a VR environment.


KONTAKT
Stephan Jonas
sjonas@mi.rwth-aachen.de

In this work, a mobile EEG headset (EMOTIV Epoc+) will be used to differentiate between positive and negative emotions in real-time. Based on existing recording applications, a real-time analysis extension will be developed that processes the EEG data in real-time and detects whether emotions are positive or negative using audio stimuli.


KONTAKT
Stephan Jonas
sjonas@mi.rwth-aachen.de

Anonymization of patient or participant data is an important step in user studies. To track participants in a long-term user observation, pseudonymization is usually employed, which allows a reconstruction of identifying user information from the pseudonym, which poses possible security and privacy risks. In this project, the aim is to evaluate a novel cryptographic anonymization process using simulation.


KONTAKT
Stephan Jonas
sjonas@mi.rwth-aachen.de