EEG artifacts detection and removal techniques for brain computer interface applications: a systematic review
Mrs Rashmi, M Mannan, M Kamran, M Jeong, M Islam, A Rastegarnia, Z Yang, X Jiang, G Bian, Z Tian, W Mumtaz, S Rasheed, A Irfan, A Tandle, N Jog, D 'cunha, P Chheta, M, J Hu, C Wang, M Wu, Y Du, Y He, J She, M Mannan, M Jeong, M Kamran, V Krishnaveni, S Jayaraman, L Anitha, K Ramadoss, D Safieddine, A Kachenoura, L Albera, G Birot, A Karfoul, A Pasnicu, A Abdullah, C Zhang, A Abdullah, S Lian, E Kroupi, A Yazdani, J Vesin, T Ebrahimi, Y Li, Z Ma, W Lu, Y Li, M Molla, M Islam, T Tanaka, T Rutkowski, V Grubov, A Runnova, A Koronovskii, A Hramov, M Quazi, S Kahalekar, S Taulu, M Kajola, J Simola, G Nolte, M Hmlinen, S Taulu, M Kajola, T Song, K Gaa, L Cui, L Feffer, R Lee, M Huang, T Song, L Cui, K Gaa, L Feffer, S Taulu, R Lee, S Taulu, R Hari, H Mki, R Ilmoniemi, J Vosskuhl, T Mutanen, T Neuling, R Ilmoniemi, C Herrmann, M Klados, C Papadelis, C Braun, P Bamidis, V Roy, S Shukla, X Chen, C He, H Peng, X Chen, Q Chen, Y Zhang, Z Wang
Abstract
Electroencephalogram (EEG) signals can be acquired using different electrodes such as dry electrodes, sticky electrodes, geltrodes etc. The placement of electrodes classifies the brain computer interface (BCI) into invasive, non-invasive and semi-invasive systems. Non-invasive is the most popular method used in medical diagnosis, research experiments and many other BCI systems as electrodes are placed on the scalp. Electrodes placed on scalp usually induce lots of artifacts to the signal by which the signal gets contaminated. These artifacts are to be removed to develop an efficient BCI system There are many methods available to detect and remove the artifacts. These methods should remove the artifacts by retaining the original neural activity of EEG signal