| Autor: |
Nekrasova, J., Bazanova, O., Shunenkov, D., Kanarskiy, M., Borisov, I., Luginina, E. |
| Předmět: |
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| Zdroj: |
Human Physiology; Aug2022, Vol. 48 Issue 4, p470-482, 13p |
| Abstrakt: |
Myogenic activity during electroencephalography is known to impose a difficult problem on any EEG investigation in the frequency-domain. It is also a serious challenge for the rising star of brain-computer interface technology. Failure to remove myogenic artefacts can lead to using myogenic signals instead of neurogenic, introduce extra variability from subject to subject, diminish the effects of neurofeedback therapy, since it is much more easier for the patient to control scalp muscles, then actual brain signals. This paper presents a deep review of high-frequency neural activity in the light of myogenic problem, different myogenic artifact correction methods, such as generalised regression, blind source separation, adaptive, Wiener and Kalman filtering and validation techniques to discern between myogenic and neurogenic signals in their pure and mixed form. Authors hope that the review can be in handy for researches, which choose the strategy for dealing with myogenic problem. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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