Automatic EEG Artifact Rejection Toolbox
(EAWICA)
EAWICA is an open source Maltlab toolbox meant for the automatic and efficient rejection of EEG artifacts.
EEG signals are automatically processed and the artifacts are detected, isolated, suppressed and the EEG is reconstructed accordingly.
The artifactual data segments are not discarded but cleaned, as described here.
If you wish to use EAWICA, you can fill the following form and receive the toolbox, I will be happy to help you to set the parameters, if needed;
As the toolbox calls the function "runica" of EEGLAB, this function is included in the toolbox and EEGLAB should be properly cited (please, visit: http://sccn.ucsd.edu/eeglab/).
EAWICA is based on the following papers (please, cite them to reference EAWICA in publications):
[1] MAMMONE N, MORABITO F C (2014). Enhanced Automatic Wavelet Independent Component Analysis for Electroencephalographic Artifact Removal. ENTROPY, vol. 16(12); p. 6553-6572, doi: doi:10.3390/e16126553
[2] MAMMONE N., LA FORESTA F, MORABITO F C (2012). Automatic Artifact Rejection from Multichannel Scalp EEG by Wavelet ICA. IEEE SENSORS JOURNAL, vol. 12(3); p. 533-542, ISSN: 1530-437X, doi: 10.1109/JSEN.2011.2115236
[3] MAMMONE N., MORABITO F C (2008). Enhanced Automatic Artifact Detection based on Independent Component Analysis and Renyi’s Entropy. NEURAL NETWORKS, vol. 21 (7); p. 1029-1040, ISSN: 0893-6080, doi: 10.1016/j.neunet.2007.09.020
[4] MAMMONE N, LAY-EKUAKILLE A., VERGALLO P., MORABITO F. C. (2014). THRESHOLD ADAPTATION IN AUTOMATIC WAVELET-ICA FOR ELECTROENCEPHALOGRAPHIC ARTIFACT REMOVAL. In: Proceedings of 3rd IMEKO TC13 SYMPOSIUM ON MEASUREMENTS IN BIOLOGY AND MEDICINE “New Frontiers in Biomedical Measurements”. Lecce, Italy, April 17-18, 2014, p. 99-104.
[5] MAMMONE N., MORABITO F C (2005). Independent Component Analysis and High-Order Statistics for Automatic Artifact Rejection. In: Proceedings of The 2005 International Joint Conference on Neural Networks. Montreal, Quebec, Canada, July 31 - August 4, vol. 4, p. 2447-2452, doi: 10.1109/IJCNN.2005.1556286
[6] LABATE D, LA FORESTA F, MAMMONE N., MORABITO F C (2015). Effects of Artifacts Rejection on EEG Complexity in Alzheimer’s Disease. Advances in Neural Networks: Computational and Theoretical Issues. vol. 37, p. 129-136.
[7] INUSO G, LA FORESTA F, MAMMONE N., MORABITO F C(2007). Brain Activity Investigation by EEG Processing: Wavelet Analysis, Kurtosis and Renyi’s Entropy for Artifact Detection. In: Proceedings of The International Conference on Information Acquisition. Jeju Island, South Korea, July 9-11, p. 195-200, doi: 10.1109/ICIA.2007.4295725
[8] INUSO G, LA FORESTA F, MAMMONE N., MORABITO F C (2007). Wavelet-ICA methodology for efficient artifact removal from Electroencephalographic recordings. In: Proceedings of The 2007 International Joint Conference on Neural Networks. Orlando, Florida, USA, August 12-17, p. 1524-1529, doi: 10.1109/IJCNN.2007.4371184
[9] MAMMONE N., INUSO G, LA FORESTA F, MORABITO F C (2007). Multiresolution ICA for Artifact Identification from Electroencephalographic Recordings. Knowledge-Based Intelligent Information and Engineering Systems. vol. 4692, p. 680-687, , doi: 10.1007/978-3-540-74819-9_84
[10] LA FORESTA F, MAMMONE N., MORABITO F C (2006). Artifact Cancellation from Electrocardiogram by Mixed Wavelet-ICA Filter. Neural Nets. vol. 3931, p. 78-82, , doi: 10.1007/11731177_12
[11] INUSO G, LA FORESTA F, MAMMONE N., MORABITO F C (2006). Automatic Detection of Critical Epochis in coma-EEG using Independent Component Analysis and Higer Order Statistics. Neural Information Processing. vol. 4234, p. 82-91, , doi: 10.1007/11893295_10
[12] La Foresta F, Inuso G, Mammone N, Morabito F C (2009). PCA-ICA for automatic identification of critical events in continuous coma-EEG monitoring. BIOMEDICAL SIGNAL PROCESSING AND CONTROL, vol. 4, p. 229-235, ISSN: 1746-8094, doi: 10.1016/j.bspc.2009.03.006