[Methods for Processing Physiological Artifacts in Single/Few-Channel EEG Signals].
Zhongguo Yi Liao Qi Xie Za Zhi
; 48(3): 298-305, 2024 May 30.
Article
en Zh
| MEDLINE
| ID: mdl-38863097
ABSTRACT
Electroencephalogram (EEG) is a non-invasive measurement method of brain electrical activity. In recent years, single/few-channel EEG has been used more and more, but various types of physiological artifacts seriously affect the analysis and wide application of single/few-channel EEG. In this paper, the regression and filtering methods, decomposition methods, blind source separation methods and machine learning methods involved in the various physiological artifacts in single/few-channel EEG are reviewed. According to the characteristics of single/few-channel EEG signals, hybrid EEG artifact removal methods for different scenarios are analyzed and summarized, mainly including single-artifact/multi-artifact scenes and online/offline scenes. In addition, the methods and metrics for validating the performance of the algorithm on semi-simulated and real EEG data are also reviewed. Finally, the development trend of single/few-channel EEG application and physiological artifact processing is briefly described.
Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Algoritmos
/
Procesamiento de Señales Asistido por Computador
/
Artefactos
/
Electroencefalografía
Límite:
Humans
Idioma:
Zh
Revista:
Zhongguo Yi Liao Qi Xie Za Zhi
Año:
2024
Tipo del documento:
Article