Sabine van Huffel - professor at the department of Electrical Engineering, Katholieke Universiteit, Leuven, Belgium - will be giving a guest lecture on Matrix/Tensor Based EEG Signal Processing: Algorithms and Applications.
In EEG signal processing, the aim is to extract clinically relevant information (e.g. rhythms, evoked potentials, bursts, seizure activity patterns) from scalp recordings in order to enable an improved medical diagnosis. Typically, EEG data are affected by artefacts (eye, muscle, etc.) and are of low quality, largely due to the non-invasive and non-obtrusive nature of the measurement process. Accurate and automated quantification of this information requires an ingenious combination of adequate pre-treatment of the data (e.g. artefact removal), feature selection, pattern recognition, decision support, up to the embedding of these advanced tools into user-friendly user interfaces to be used by clinicians.
The underlying computational signal processing problems can be solved by making use of matrix and tensor decompositions. In particular, it is shown how Principal Component Analysis, Canonical Correlation Analysis, Independent component Analysis, Parallel Factor Analysis and Block Component Analysis, can be used as building blocks of higher-level signal processing algorithms. In addition, the application of these decompositions and their benefits will be illustrated in a variety of case studies, including epileptic seizure onset localisation using adult and neonatal scalp EEG and Event-related potential analysis during simultaneous EEG-fMRI acquisition.
The lecture will take place at DTU in Building 349, room 205 at 10:00-11:00 hours
For further information, please contact:
Assoc. Professor Ph.D. Helge B.D. Sørensen, Department of Electrical Engineering, DTU,