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A pulse artifact removal method considering artifact variations in the simultaneous recording of EEG and fMRI.
Oh, Sung Suk; Han, Yeji; Lee, Jongho; Yun, Seong Dae; Kang, Joong Koo; Lee, Eun Mi; Yoon, Hyo Woon; Chung, Jun-Young; Park, HyunWook.
Afiliación
  • Oh SS; Department of Electrical Engineering, Korean Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.
  • Han Y; Department of Electrical Engineering, Korean Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea; Department of Biomedical Engineering, College of Health Science, Gachon University, Incheon, Republic of Korea.
  • Lee J; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.
  • Yun SD; Department of Electrical Engineering, Korean Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
  • Kang JK; Department of Neurology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea.
  • Lee EM; Department of Neurology, University of Ulsan College of Medicine, Ulsan University Hospital, Ulsan, Republic of Korea.
  • Yoon HW; Department of Art Therapy, Daegu Cyber University, Daegu, Republic of Korea.
  • Chung JY; Department of Biomedical Engineering, College of Health Science, Gachon University, Incheon, Republic of Korea. Electronic address: jychung@gachon.ac.kr.
  • Park H; Department of Electrical Engineering, Korean Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. Electronic address: hwpark@kaist.ac.kr.
Neurosci Res ; 81-82: 42-50, 2014.
Article en En | MEDLINE | ID: mdl-24487121
ABSTRACT
A simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) can provide high spatiotemporal information of brain activity. However, a proper analysis of the EEG signals is often hindered by various artifacts. In particular, pulse artifact (PA) induced from the heartbeat of a subject interferes with reliable measurements of the EEG signal. A new PA removal method that takes into account the delay variation between the heartbeat and PA and the window size variation in PA is presented in order to improve the detection and suppression of PA in EEG signals. A PA is classified into either a normal PA or a deformed PA. Only normal PAs are averaged to generate a PA template that is used to remove PAs from the measured EEG signals. The performance of the proposed method was evaluated by simulated data and real EEG measurements from epilepsy patients. The results are compared with those from conventional methods.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Imagen por Resonancia Magnética / Artefactos / Electroencefalografía Límite: Adult / Female / Humans / Male Idioma: En Revista: Neurosci Res Asunto de la revista: NEUROLOGIA Año: 2014 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Imagen por Resonancia Magnética / Artefactos / Electroencefalografía Límite: Adult / Female / Humans / Male Idioma: En Revista: Neurosci Res Asunto de la revista: NEUROLOGIA Año: 2014 Tipo del documento: Article País de afiliación: Estados Unidos