As a biomedical engineer I am interested in the advancement of the Engineering Profession in general, and the Biomedical Engineering Profession specifically. My research centers around the use of intelligent signal processing techniques in the analysis of biomedical signals. In particular I am interested in the analysis of the electromagnetic activity recorded from the brain - in the form of the electroencephalogram (EEG) and magnetoencephalogram (MEG). The EEG in particular is a useful diagnostic tool in field of epilepsy.
The analysis techniques of choice are sometimes referred to Computational Intelligence techniques which include such as the use of Artificial Neural Networks, Fuzzy Logic and Fuzzy Inference. I also have a great interest in the self-organised discovery of information from biomedical data using clustering techniques such as the Self-Organising Feature Map (SOFM), Generative Topographic Mapping (GTM) and Neuroscale.
I have a particular interest in the use of Blind Source Separation (BSS) techniques, such Independent Component Analysis (ICA), in the analysis of both single-channel and multi-channel recordings of biomedical signals.
My research has 3 facets:
The development of advanced BSS techniques.
The application of these techniques to real-world problems in biomedicine.
Applications specifically in Neural Engineering
The many areas of research in BSS and ICA are listed below:
The real-world biomedical applications are as listed below:
In Neural Engineering I work in the following key areas, and each of these areas of application has impact on the analysis techniques listed: