From wavelets to adaptive approximations: time-frequency parametrization of EEG.
This paper presents a summary of time-frequency analysis of the electrical activity of the brain (EEG). It covers in details two major steps: introduction of wavelets and adaptive approximations. Presented studies include time-frequency solutions to several standard research and clinical problems, encountered in analysis of evoked potentials, sleep EEG, epileptic activities, ERD/ERS and pharmaco-EEG. Based upon these results we conclude that the matching pursuit algorithm provides a unified parametrization of EEG, applicable in a variety of experimental and clinical setups. This conclusion is followed by a brief discussion of the current state of the mathematical and algorithmical aspects of adaptive time-frequency approximations of signals.
Durka
Piotr J
PJ
Laboratory of Medical Physics, Institute of Experimental Physics, Warsaw University, Warszawa, Poland. piotr@durka.info
D000465:Algorithms; D004569:Electroencephalography / Q000592:standards; D005071:Evoked Potentials; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007091:Image Processing, Computer-Assisted; D008874:Midazolam / Q000494:pharmacology; D008962:Models, Theoretical; D011725:Pyridines / Q000494:pharmacology; D012815:Signal Processing, Computer-Assisted; D012890:Sleep / Q000187:drug effects / Q000502:physiology; D013269:Stochastic Processes; D013997:Time Factors; D000077334:Zolpidem
D011725:Pyridines; D000077334:Zolpidem; D008874:Midazolam