An adaptive noise canceller based on QLMS algorithm for removing EOG artifacts in EEG recordings
Küçük Resim Yok
Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this paper, a novel adaptive noise canceller (ANC) based on the quaternion valued least mean square algorithm (QLMS) is designed in order to remove electrooculography (EOG) artifacts from electroencephalography (EEG) recordings. The measurement real-valued EOG and EEG signals (FP1, FP2, AF3 and AF4) are first modeled as four-dimensional processes in the quaternion domain. The EOG artifacts are then removed from the EEG signals in the quaternion domain by using the ANC based on QLMS algorithm. The quaternion representation of these signals allows us to remove EOG artifacts from all channels at the same time instead of removing the EOG artifacts in each EEG recordings separately. The simulation results support the proposed approach. © 2017 IEEE.
Açıklama
2017 International Artificial Intelligence and Data Processing Symposium, IDAP 2017 -- 16 September 2017 through 17 September 2017 -- -- 115012
Anahtar Kelimeler
Adaptive noise canceller, EEG and EOG signals, Quaternion domain, Quaternion least mean square
Kaynak
IDAP 2017 - International Artificial Intelligence and Data Processing Symposium
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
