What does clean EEG look like
作者： I. Daly , F. Pichiorri , J. Faller , V. Kaiser , A. Kreilinger
DOI: 10.1109/EMBC.2012.6346834
关键词: Eeg analysis 、 Artificial intelligence 、 Thresholding 、 EEG-fMRI 、 Artifact (error) 、 Neurophysiology 、 Metric (mathematics) 、 Neuroscience 、 Electroencephalography 、 Pattern recognition 、 Healthy subjects 、 Psychology
摘要: Lack of a clear analytical metric for identifying artifact free, clean electroencephalographic (EEG) signals inhibits robust comparison different removal methods and lowers confidence in the results EEG analysis. An algorithm is presented epochs by thresholding statistical properties EEG. Thresholds are trained on datasets from both healthy subjects stroke / spinal cord injury patient populations via differential evolution (DE).
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