Title :
What does clean EEG look like?
Author :
Daly, Ian ; Pichiorri, F. ; Faller, Josef ; Kaiser, V. ; Kreilinger, A. ; Scherer, Rafal ; Muller-Putz, G.
Author_Institution :
Lab. of Brain-Comput. Interfaces, Graz Univ. of Technol., Graz, Austria
fDate :
Aug. 28 2012-Sept. 1 2012
Abstract :
Lack of a clear analytical metric for identifying artifact free, clean electroencephalographic (EEG) signals inhibits robust comparison of different artifact removal methods and lowers confidence in the results of EEG analysis. An algorithm is presented for identifying clean EEG epochs by thresholding statistical properties of the EEG. Thresholds are trained on EEG datasets from both healthy subjects and stroke/spinal cord injury patient populations via differential evolution (DE).
Keywords :
diseases; electroencephalography; injuries; medical signal processing; neurophysiology; statistical analysis; EEG; artifact removal methods; differential evolution; signal cleaning; spinal cord injury; statistical properties; stroke; Accuracy; Electrodes; Electroencephalography; Noise; Pollution measurement; Standards; Artifacts; Electroencephalography; Female; Humans; Male; Middle Aged; Signal Processing, Computer-Assisted; Young Adult;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-4119-8
Electronic_ISBN :
1557-170X
DOI :
10.1109/EMBC.2012.6346834
