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Published in 2022 at "IEEE Transactions on Neural Systems and Rehabilitation Engineering"
DOI: 10.1109/tnsre.2022.3182705
Abstract: Monitoring the consciousness states of patients and ensuring the appropriate depth of anesthesia (DOA) is critical for the safe implementation of surgery. In this study, a high-density electroencephalogram (EEG) combined with blood drug concentration and…
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Keywords:
state;
brain consciousness;
brain;
propofol induced ... See more keywords
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Published in 2018 at "Frontiers in Computational Neuroscience"
DOI: 10.3389/fncom.2018.00070
Abstract: We analyse statistical and information-theoretical properties of EEG microstate sequences, as seen through the lens of five different clustering algorithms. Microstate sequences are computed for n = 20 resting state EEG recordings during wakeful rest.…
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Keywords:
microstate;
information;
time;
clustering algorithms ... See more keywords
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Published in 2018 at "Frontiers in Neuroinformatics"
DOI: 10.3389/fninf.2018.00030
Abstract: We present an open-source Python package to compute information-theoretical quantities for electroencephalographic data. Electroencephalography (EEG) measures the electrical potential generated by the cerebral cortex and the set of spatial patterns projected by the brain's electrical…
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Keywords:
information;
information theoretical;
time;
microstate sequences ... See more keywords
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Published in 2022 at "Frontiers in Psychology"
DOI: 10.3389/fpsyg.2022.1065196
Abstract: Recognizing emotion from Electroencephalography (EEG) is a promising and valuable research issue in the field of affective brain-computer interfaces (aBCI). To improve the accuracy of emotion recognition, an emotional feature extraction method is proposed based…
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Keywords:
emotion recognition;
emotion;
microstate sequences;
feature extraction ... See more keywords