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.
- Reimplement the OrganChallenge framework in .NET
- Implement additional games
- Evaluate usability and learning effectiveness
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).
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/
In this thesis we will explore the possibilities of deep learning to detect abnormalities in human electroencephalogram (EEG). The methods currently used in natural language processing such as recurrent neural networks (RNN) have a high application potential for time series data such as EEG.