Reliable and fast automatic artifact rejection of Long-Term EEG recordings based on Isolation Forest.

Zhang, Runkai; Rong, Rong; Gan, John Q; Xu, Yun; Wang, Haixian; Wang, Xiaoyun

Zhang, Runkai; Rong, Rong; Gan, John Q; Xu, Yun; Wang, Haixian; Wang, Xiaoyun.

Afiliación

Zhang R; Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science & Medical Engineering, Southeast University, Nanjing, 210096, Jiangsu, People's Republic of China.
Rong R; Department of Neurology, Nanjing Drum Tower Hospital, Nanjing, 210008, Jiangsu, People's Republic of China.
Gan JQ; School of Computer Science and Electronic Engineering, University of Essex, Colchester, CO4 3SQ, UK.
Xu Y; Department of Neurology, Nanjing Drum Tower Hospital, Nanjing, 210008, Jiangsu, People's Republic of China.
Wang H; Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science & Medical Engineering, Southeast University, Nanjing, 210096, Jiangsu, People's Republic of China. hxwang@seu.edu.cn.
Wang X; Department of Neurology, Nanjing Drum Tower Hospital, Nanjing, 210008, Jiangsu, People's Republic of China. xysypy@126.com.

Med Biol Eng Comput ; 62(2): 521-535, 2024 Feb.

Article en En | MEDLINE | ID: mdl-37943419

Asunto(s)

Artefactos; Procesamiento de Señales Asistido por Computador; Humanos; Estudios Retrospectivos; Algoritmos; Electroencefalografía/métodos

Palabras clave

Automatic rejection; Isolation Forest; Long-Term EEG; Machine learning; Outlier detection

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Procesamiento de Señales Asistido por Computador / Artefactos Límite: Humans Idioma: En Revista: Med Biol Eng Comput Año: 2024 Tipo del documento: Article

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