Noise removal methods on ambulatory EEG: A Survey
This is an incremental survey paper that reviews existing methods for noise removal in ambulatory EEG, which is important for researchers and practitioners in biomedical signal processing.
The paper surveys over 100 research papers on noise removal methods for ambulatory EEG, highlighting that pattern recognition techniques vary with different EEG dataset conditions to effectively distinguish noise.
Over many decades, research is being attempted for the removal of noise in the ambulatory EEG. In this respect, an enormous number of research papers is published for identification of noise removal, It is difficult to present a detailed review of all these literature. Therefore, in this paper, an attempt has been made to review the detection and removal of an noise. More than 100 research papers have been discussed to discern the techniques for detecting and removal the ambulatory EEG. Further, the literature survey shows that the pattern recognition required to detect ambulatory method, eye open and close, varies with different conditions of EEG datasets. This is mainly due to the fact that EEG detected under different conditions has different characteristics. This is, in turn, necessitates the identification of pattern recognition technique to effectively distinguish EEG noise data from a various condition of EEG data.