학술논문

Removing EOG Artifacts from the Resting State EEG Signal of Methamphetamine Addicts by ICA Algorithms
Document Type
Conference
Source
2023 11th International Winter Conference on Brain-Computer Interface (BCI) Brain-Computer Interface (BCI), 2023 11th International Winter Conference on. :1-5 Feb, 2023
Subject
Bioengineering
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Electrooculography
Brain
Electroencephalography
Brain-computer interfaces
Recording
Time-domain analysis
EEG
Artifact removal
Independent component analysis (ICA)
EOG
Language
ISSN
2572-7672
Abstract
EEG signal contains a wealth of information about brain activity, but the recording process is inevitably contaminated by EOG artifacts. An effective method to remove EOG artifacts can provide a guarantee for subsequent EEG analysis. In this paper, we compare the performance of four ICA algorithms in removing EOG artifacts from EEG signals of methamphetamine addicts. From the perspective of time domain and power spectral density, all the four algorithms can effectively remove the EOG artifacts without obvious difference. In terms of PSNR, MI and processing speed, FastICA algorithm can achieve higher processing speed and reconstruct signals better than the other three algorithms.