The performance of electroencephalography (EEG) data depends on the effective attenuation of artifacts that are mixed in the recordings. To address this problem, we have developed a novel online EEG artifact removal method for online applications, which combines Independent Component Analysis (ICA) and regression (REG) analysis. ICA-REG method relies on the availability of a calibration dataset of limited duration for the initialization of a spatial filter using ICA. Online artifact removal is implemented by dynamically adjusting the spatial filter in the actual experiment, based on linear regression.

This software can be used to do a pseudo-online artifact removal (necessary for the validations in your project), or a real-time filtering, or to filter the whole signal offline.

For support: roberto.guarnieri@kuleuven.be

To cite this software: http://iopscience.iop.org/article/10.108...
Roberto Guarnieri et al 2018 J. Neural Eng. 15 056009