Notice of Removal: Removal of ocular artifacts using ICA and adaptive filter for motor imagery-based BCI

Abstract

Preprocessing is the first step of Brain Computer Interface U+0028 BCI U+0029 based on Electroencephalogram U+0028 EEG U+0029, the most important aspect in this step is to remove Ocular Artifacts U+0028 OAs U+0029 included in EEG signals. OAs are the main interference signals to the EEG signals. In this paper, a new method called ICA-AF is proposed. This method using Independent Component Analysis U+0028 ICA U+0029 and Adaptive Filter U+0028 AF U+0029 can remove OAs from the EEG signals without measuring Electrooculogram U+0028 EOG U+0029. The method firstly decomposes the multi-channel EEG signals into the statistically independent components by ICA, then extracts the exact OAs that do not include the brain activity information in the OA-related independent components, and converts the exact OAs to the OAs at each electrode using inverse ICA U+0028 iICA U+0029. An adaptive filter uses this OA and the EEG signal in each channel as reference and input signal, respectively. Compared to ICA and ICA-RLS U+0028 Independent Component Analysis-Robust Least Square U+0029 methods, the proposed method can remove most of exact OAs and preserve as much brain activity information as possible. In addition, the average classification accuracy of the new method is 19 U+0025 and 8 U+0025 higher than the previous two methods, in the ratio of the average classification accuracy of the raw EEG, respectively. Besides, the new method is 1.45 times faster than ICA-RLS method, with respect to the execution time of ICA method.