Overview
The BIOMED research - fundamental/theoretical as well as application oriented - is performed in the domain of (multi)linear algebra, (non)linear signal analysis,
classification and system identification with special focus on the development of numerically reliable and robust algorithms for improving medical diagnostics. In this domain the group has built up an international reputation.
Applications under study are: in-vivo Magnetic Resonance Spectroscopic (MRS) data quantitaion and imaging, neonatal brain oxygenation and autoregulation, heart-rate variability analysis, epileptic seizure detection and localization using scalp-EEG, EMG based stress monitoring, computer-aided (brain, ovarian, prostate) cancer diagnosis, integrated EEG-functional MRI (fMRI) data processing, multimodal MRS-MRI processing for brain tumour recognition.
Current challenges:
- Improved objective diagnosis via automated integration of all available information (multichannel, multimodal, low signal-to-noise ratio, high variability, prior knowledge, nonstationarity, nonlinearity).
- Tensor extensions of matrix techniques (such as low rank approximation, Singular Value Decomposition and Principal Component Analysis) and corresponding numerical software for biomedical multimodal and multichannel processing.
- Integrated multimodal data processing, analysis and decision support for simultaneously acquired biomedical data such as EEG, MEG, ECG, EMG, EOG, fMRI, MRSI, MRI, PET and SPECT.
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Overview 
