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A pulse artifact removal method considering artifact variations in the simultaneous recording of EEG and fMRI
Affiliation:1. Department of Electrical Engineering, Korean Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea;2. Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA;3. Department of Neurology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea;4. Department of Neurology, University of Ulsan College of Medicine, Ulsan University Hospital, Ulsan, Republic of Korea;5. Department of Art Therapy, Daegu Cyber University, Daegu, Republic of Korea;6. Department of Biomedical Engineering, College of Health Science, Gachon University, Incheon, Republic of Korea;1. Departments of Bioengineering, College of Engineering, and BK21 PLUS Future Biopharmaceutical Human Resources Training and Research Team, and Institute of Nano Science & Technology (INST), Hanyang University, Seoul 04763, Republic of Korea;2. Department of Radiology, Asan Medical Center, University of Ulsan, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Republic of Korea;1. Department of Applied Statistics, University of Suwon, Gyeonggi-Do 445-743, Republic of Korea;2. Clinical Trials Center Severance Hospital, Yonsei University Health System, Seoul 120-749, Republic of Korea;3. Department of Applied Mathematics, Hanyang University, Gyeonggi-Do 426-791, Republic of Korea;1. Department of Surgery, Shanghai Jiao Tong University Affiliated Sixth People''s Hospital, Shanghai, China;2. Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea;1. Department of Applied Social Sciences, The Hong Kong Polytechnic University, Hong Kong, P.R. China;2. Centre for Innovative Programmes for Adolescents and Families, The Hong Kong Polytechnic University, Hong Kong, P.R. China;3. Department of Social Work, East China Normal University, Shanghai, P.R. China;4. Kiang Wu Nursing College of Macau, Macau, P.R. China;1. RIKEN Brain Science Institute, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan;2. Graduate School of Science and Engineering, Tokyo Institute of Technology, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan;3. Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea;1. Department of Radiation Oncology, Wonju College of Medicine, Yonsei University, Wonju 26426, Republic of Korea;2. Department of Microbiology, Wonju College of Medicine, Yonsei University, Wonju 26426, Republic of Korea;3. Institute of Genomic Cohort, Wonju College of Medicine, Yonsei University, Wonju 26426, Republic of Korea;4. Department of Microbiology and Institute for Clinical and Translational Research, Catholic Kwandong University College of Medicine, Gangneung 25601, Republic of Korea
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.
Keywords:Individual delay and window size  Intractable partial epilepsy patients  Pulse artifact (PA)  Simultaneous EEG and fMRI
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