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dc.contributor.authorMelia, Umberto
dc.contributor.authorClarià Sancho, Francisco
dc.contributor.authorVallverdú, Montserrat
dc.contributor.authorCaminal Magrans, Pere
dc.description.abstractTo remove peak and spike artifacts in biological time series has represented a hard challenge in the last decades. Several methods have been implemented mainly based on adaptive filtering in order to solve this problem. This work presents an algorithm for removing peak and spike artifacts based on a threshold built on the analytic signal envelope. The algorithm was tested on simulated and real EEG signals that contain peak and spike artifacts with random amplitude and frequency occurrence. The performance of the filter was compared with commonly used adaptive filters. Three indexes were used for testing the performance of the filters: Correlation coefficient, mean of coherence function, and rate of absolute error. All these indexes were calculated between filtered signal and original signal without noise. It was found that the new proposed filter was able to reduce the amplitude of peak and spike artifacts with > 0.85, C > 0.8, and RAE < 0.5. These values were significantly better than the performance of LMS adaptive filter ( < 0.85, C < 0.6, and RAE > 1).
dc.relation.isformatofVersió postprint del document publicat a:
dc.relation.ispartofMedical Engineering & Physics, 2014, vol. 36, num. 4, p. 547-553
dc.rightscc-by-nc-nd (c) Elsevier, 2014
dc.subjectProcesado de señales biomédicas
dc.subjectIngeniería biomédica
dc.subjectBiomedical signal processing
dc.subjectDigital filters
dc.subject.classificationEnginyeria biomèdica
dc.subject.otherBiomedical engineering
dc.titleFiltering and thresholding the analytic signal envelope in order to improve peak and spike noise reduction in EEG signals

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cc-by-nc-nd (c) Elsevier, 2014
Except where otherwise noted, this item's license is described as cc-by-nc-nd (c) Elsevier, 2014