TY - GEN
T1 - Real-time detection and filtering of eye movement and blink related artifacts in EEG
AU - Binias, Bartosz
AU - Palus, Henryk
AU - Jaskot, Krzysztof
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/9/29
Y1 - 2015/9/29
N2 - Eye movement related artifacts are the most significant source of noise in EEG signals. Thus, a special approach to reduction of their influence is required. However, most of currently used methods of detecting and filtering eye movement related artifacts require either an additional recording of noise signal, or are not suitable for real time applications, such as Brain-Computer Interfaces. In this paper it was proven that it is possible to detect and filter those artifacts in real time, without the need of providing an additional recording of noise signal.
AB - Eye movement related artifacts are the most significant source of noise in EEG signals. Thus, a special approach to reduction of their influence is required. However, most of currently used methods of detecting and filtering eye movement related artifacts require either an additional recording of noise signal, or are not suitable for real time applications, such as Brain-Computer Interfaces. In this paper it was proven that it is possible to detect and filter those artifacts in real time, without the need of providing an additional recording of noise signal.
UR - https://www.scopus.com/pages/publications/84964465113
U2 - 10.1109/MMAR.2015.7283997
DO - 10.1109/MMAR.2015.7283997
M3 - Conference contribution
AN - SCOPUS:84964465113
T3 - 2015 20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015
SP - 903
EP - 908
BT - 2015 20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015
Y2 - 24 August 2015 through 27 August 2015
ER -