NDLI: Adaptive multiresolutiion analysis based evoked potential filtering

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Adaptive multiresolutiion analysis based evoked potential filtering

Content Provider	Semantic Scholar
Author	Saatchi, M. R. Gibson, Christopher Rowe, John Allen, E. M.
Copyright Year	2004
Abstract	Evoked potentials (EPs) are electrical activities of the brain synchronised with external stimuli. They have proved valuable for the understanding of the functioning of the brain and in investigating several brain related disorders. EPs are usually obscured by the background electroencephalogram (EEG) and thus require appropriate filtering. As the frequency spectra of the EEG and EPs overlap, the application of deterministic filters on their own is usually inadequate. Synchronised averaging improves the signal-to-noise ratio; however it inhibits measurement of the important variations which develop from one EP recording or trial to the next. The presence of these variations also makes an averaged EP a distorted version of an EP which evolves with time. A novel adaptive filtering algorithm based on the wavelet transform method of multiresolution analysis (MRA) was developed and was successfully used for single trial recovery of a type of EP known as the contingent negative variation (CNV). Bloth simulated and real CNV waveforms were processed. A technique to evaluate the effectiveness of the developed method was devised and was used to select the best orthogonal filter among Daubechies, Coifman and Symmlet for the adaptive MRA based filtering operation. ‘The technique enabled the magnitude of the background EEG to be reduced by a factor of 5 while preserving the main features of the CNV waveform.
File Format	PDF HTM / HTML
Language	English
Access Restriction	Open
Subject Keyword	Acoustic Evoked Brain Stem Potentials Action potential Adaptive filter Algorithm Contingency (philosophy) Contingent Negative Variation Copy Number Polymorphism Electroencephalography Phase Synchronization Evoked Potentials Expectation propagation Multiresolution analysis Schizophrenia Signal-to-noise ratio Waveform Wavelet transform
Content Type	Text
Resource Type	Article

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