CLEANED EEG SIGNAL: AUTOMATIC EEG ARTIFACT REMOVAL FOR BRAIN MONITORING
| Main Author: | Govind M*1 & Deepa T R 2* |
|---|---|
| Format: | Article |
| Terbitan: |
, 2019
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/2631569 |
Daftar Isi:
- An effective method for removal of noises in Electroencephalogram was developed and evaluated. This noise is called artifacts in EEG signal. The method targets most types of artifacts and works without user interaction. The method uses the neurophysiologic model of EEG signal and an iterative Bayesian estimation scheme. Artifact removal algorithm effectively removes artifacts from EEGs and improves the quality of EEG signal impaired by artifacts. Only in rare cases did the algorithm slightly attenuate EEG patterns, but the clear visibility of significant patterns was preserved. Artifact removal methods work either semi-automatically or with insufficient reliability for clinical use, whereas the clean EEG method works fully automatically and leaves true EEG patterns unchanged with a high reliability. The artifact removal algorithm removes noise with less amount of time. Here the classification of EEG bands are considered for effective monitoring of human brain.