Filtering and thresholding the analytic signal envelope in order to improve peak and spike noise reduction in EEG signals
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...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2014 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/23370 |
| Acceso en línea: | https://hdl.handle.net/2117/23370 https://dx.doi.org/10.1016/j.medengphy.2013.11.014 |
| Access Level: | acceso abierto |
| Palabra clave: | Electroencephalography Biomedical signal processing Digital filters EVENT-RELATED POTENTIALS REMOVING ARTIFACTS FREQUENCY-DOMAIN EOG ARTIFACTS ELECTROENCEPHALOGRAM RECORDINGS ALGORITHM SEIZURES Electroencefalografia Àrees temàtiques de la UPC::Informàtica::Automàtica i control Àrees temàtiques de la UPC::Enginyeria biomèdica::Electrònica biomèdica |
| Sumario: | 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 (p), 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 rho > 0.85, C > 0.8, and RAE < 0.5. These values were significantly better than the performance of LMS adaptive filter (rho < 0.85, C < 0.6, and RAE > 1). |
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