Ongoing EEG artifact correction using blind source separation.
Clin Neurophysiol
; 158: 149-158, 2024 02.
Article
en En
| MEDLINE
| ID: mdl-38219404
ABSTRACT
OBJECTIVE:
Analysis of the electroencephalogram (EEG) for epileptic spike and seizure detection or brain-computer interfaces can be severely hampered by the presence of artifacts. The aim of this study is to describe and evaluate a fast automatic algorithm for ongoing correction of artifacts in continuous EEG recordings, which can be applied offline and online.METHODS:
The automatic algorithm for ongoing correction of artifacts is based on fast blind source separation. It uses a sliding window technique with overlapping epochs and features in the spatial, temporal and frequency domain to detect and correct ocular, cardiac, muscle and powerline artifacts.RESULTS:
The approach was validated in an independent evaluation study on publicly available continuous EEG data with 2035 marked artifacts. Validation confirmed that 88% of the artifacts could be removed successfully (ocular 81%, cardiac 84%, muscle 98%, powerline 100%). It outperformed state-of-the-art algorithms both in terms of artifact reduction rates and computation time.CONCLUSIONS:
Fast ongoing artifact correction successfully removed a good proportion of artifacts, while preserving most of the EEG signals.SIGNIFICANCE:
The presented algorithm may be useful for ongoing correction of artifacts, e.g., in online systems for epileptic spike and seizure detection or brain-computer interfaces.Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Procesamiento de Señales Asistido por Computador
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Artefactos
Tipo de estudio:
Clinical_trials
Límite:
Humans
Idioma:
En
Revista:
Clin Neurophysiol
/
Clin. neurophysiol
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Clinical neurophysiology
Asunto de la revista:
NEUROLOGIA
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PSICOFISIOLOGIA
Año:
2024
Tipo del documento:
Article