title: Hybrid EEG--Eye Tracker: Automatic Identification and Removal of Eye Movement and Blink Artifacts from Electroencephalographic Signal.
abstract: Contamination of eye movement and blink artifacts in Electroencephalogram (EEG) recording makes the analysis of EEG data more difficult and could result in mislead findings. Efficient removal of these artifacts from EEG data is an essential step in improving classification accuracy to develop the brain-computer interface (BCI). In this paper, we proposed an automatic framework based on independent component analysis (ICA) and system identification to identify and remove ocular artifacts from EEG data by using hybrid EEG and eye tracker system. The performance of the proposed algorithm is illustrated using experimental and standard EEG datasets. The proposed algorithm not only removes the ocular artifacts from artifactual zone but also preserves the neuronal activity related EEG signals in non-artifactual zone. The comparison with the two state-of-the-art techniques namely ADJUST based ICA and REGICA reveals the significant improved performance of the proposed algorithm for removing eye movement and blink artifacts from EEG data. Additionally, results demonstrate that the proposed algorithm can achieve lower relative error and higher mutual information values between corrected EEG and artifact-free EEG data.
authors.affiliation: Department of Cogno-Mechatronics Engineering, Pusan National University, 2 Busandaehak-ro 63beon-gil Geumjeong-gu, Busan 609-735, Korea. naeem@pusan.ac.kr.
authors.forename: Malik M Naeem
authors.initials: MM
authors.lastname: Mannan
authors.affiliation: Department of Cogno-Mechatronics Engineering, Pusan National University, 2 Busandaehak-ro 63beon-gil Geumjeong-gu, Busan 609-735, Korea. shinjungkim@pusan.ac.kr.
authors.forename: Shinjung
authors.initials: S
authors.lastname: Kim
authors.affiliation: Department of Cogno-Mechatronics Engineering, Pusan National University, 2 Busandaehak-ro 63beon-gil Geumjeong-gu, Busan 609-735, Korea. myjeong@pusan.ac.kr.
authors.forename: Myung Yung
authors.initials: MY
authors.lastname: Jeong
authors.affiliation: Department of Cogno-Mechatronics Engineering, Pusan National University, 2 Busandaehak-ro 63beon-gil Geumjeong-gu, Busan 609-735, Korea. malik@pusan.ac.kr.
authors.forename: M Ahmad
authors.initials: MA
authors.lastname: Kamran
mesh_terms: D000465:Algorithms; D062207:Brain-Computer Interfaces; D004569:Electroencephalography / Q000379:methods*; D004585:Electrooculography / Q000379:methods*; D005133:Eye Movements / Q000502:physiology; D006801:Humans; D012815:Signal Processing, Computer-Assisted
keywords: affine projection algorithm; auto-regressive exogenous model; composite multi-scale entropy; electroencephalogram; eye tracker; independent component analysis; median absolute deviation; ocular artifacts