title: Filtering and thresholding the analytic signal envelope in order to improve peak and spike noise reduction in EEG signals.
abstract: To 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 (ρ), mean of coherence function (C), and rate of absolute error (RAE). 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 ρ>0.85, C>0.8, and RAE<0.5. These values were significantly better than the performance of LMS adaptive filter (ρ<0.85, C<0.6, and RAE>1).
authors.affiliation: Department of ESAII, Centre for Biomedical Engineering Research, Universitat Politècnica de Catalunya, CIBER of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain. Electronic address: umberto.melia@upc.edu.
authors.forename: Umberto
authors.initials: U
authors.lastname: Melia
authors.affiliation: Department of IIE, Lleida University, Spain. Electronic address: claria@diei.udl.es.
authors.forename: Francesc
authors.initials: F
authors.lastname: Clariá
authors.affiliation: Department of ESAII, Centre for Biomedical Engineering Research, Universitat Politècnica de Catalunya, CIBER of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain. Electronic address: montserrat.vallverdu@upc.edu.
authors.forename: Montserrat
authors.initials: M
authors.lastname: Vallverdú
authors.affiliation: Department of ESAII, Centre for Biomedical Engineering Research, Universitat Politècnica de Catalunya, CIBER of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain. Electronic address: pere.caminal@upc.edu.
authors.forename: Pere
authors.initials: P
authors.lastname: Caminal
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001921:Brain / Q000502:physiology; D003198:Computer Simulation; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D012815:Signal Processing, Computer-Assisted
keywords: Biomedical signal processing; Digital filters; Electroencephalography