“Source Separation for Biomedical Signals: Blind or not Blind?" Dr. Christian Jutten (BIOSTEC 2013)
Keynote Title: The Application of Biomedical Instrumentation for Sensory-Motor Recovery and Functional Assessment in Spinal Cord Injured Individuals
Keynote Lecturer: Dr. Christian Jutten
Keynote Chair: Dr. Adam Kampff
Presented on: 12-02-2013
Abstract: Source separation is a fundamental problem in signal processing. In early 80's, independent component analysis (ICA) have been developed for solving this problem, with very weak priors on sources hence the name "blind". ICA was then successfully applied in middle of 90 to biomedical signals, like ECG, EEG, MRI, etc. But, in fact, each class of biomedical signals has usually known properties, which can be used as priors in source separation, and in addition (or instead) to source independence which is not always satisfied. Usual priors can be properties in frequency or time domains, model of sources. Using such priors, the source separation problem becomes semi-blind (or not blind at all !) and one can consider (or design) methods which are simpler and more efficient than ICA. In this talk, I first explain the main theoretical results for solving source separation using ICA or methods based on various priors. Then, I illustrate the various approaches proposed in the theoretical framework with a few examples in biomedical signal processing. The talk will finish with a discussion on a few open questions.
Presented at the following Conference: BIOSTEC, International Joint Conference on Biomedical Engineering Systems and Technologies
Conference Website: biostec.org