A robust method to filter various types of artifacts on long duration EEG recordings

摘要：

EEG is a system used to measure electrical brain activity using multiple electrodes placed on the scalp. Unfortunately, the signals can be easily contaminated by noises called artifacts. These can be generated by various actions such as eye blinks, eye movements, muscle activities or small electrode movements. This paper presents a global artifact removal method corresponding to an evolution of the AFOP method (Adaptive Filtering by Optimal Projection) in order to improve its stability. This evolution automatically filters ocular, muscular and heart beat artifacts. The results are validated on long duration EEG recordings containing pathological activities. An expert analysis shows that the cerebral signal is well conserved while a lot of artifacts are removed.

作者: Samuel Boudet Laurent Peyrodie Philippe Gallois Christian Vasseur

作者单位: HEI-ERASM (Hautes Etudes dIng′enieur) and LAGIS, Lille, 59000, France St Vincent Hospital, Lille, France LAGIS UMR-CNRS 8146, University of Lille1, Villeneuve dAscq, 59655, France

会议类型: 国际会议

会议名称: The 2nd International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2008)(第二届生物信息与生物医学工程国际会议)

会议地点: 上海

会议语种:英文

页码: 2379-2382

在线出版日期: 2008-05-16（万方平台首次上网日期，不代表论文的发表时间）