@inproceedings{96e528090c17496e88fa4f45cdf8dd7f,
title = "Artifacts reduction method in EEG signals with wavelet transform and adaptive filter",
abstract = "This paper presents a method to remove ocular artifacts from electroencephalograms (EEGs) which can be used in biomedical analysis in portable environment. An important problem in EEG analysis is how to remove the ocular artifacts which wreak havoc among analyzing EEG signals. In this paper, we propose a combination of Wavelet Transform with effective threshold and adaptive filter which can extract the reference signal according to ocular artifacts distributing in low frequency domain mostly, and adaptive filter based on Least Mean Square (LMS) algorithm is used to remove ocular artifacts from recorded EEG signals. The results show that this method can remove ocular artifacts and superior to a comparison method on retaining uncontaminated EEG signal. This method is applicable to the portable environment, especially when only one channel EEG are recorded.",
keywords = "adaptive filter, electroencephalogram (EEG), ocular artifacts, signal processing",
author = "Rui Huang and Fei Heng and Bin Hu and Hong Peng and Qinglin Zhao and Qiuxia Shi and Jun Han",
year = "2014",
doi = "10.1007/978-3-319-09891-3_12",
language = "English",
isbn = "9783319098906",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "122--131",
booktitle = "Brain Informatics and Health - International Conference, BIH 2014, Proceedings",
address = "Germany",
note = "2014 International Conference on Brain Informatics and Health, BIH 2014 ; Conference date: 11-08-2014 Through 14-08-2014",
}