Real‐time ballistocardiographic artifact reduction using the k‐teager energy operator detector and multi‐channel referenced adaptive noise cancelling |
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| Authors: | Xiaotong Wen Mingxuan Kang Li Yao Xiaojie Zhao |
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| Affiliation: | 1. Department of Psychology, Renmin University of China, China;2. State Key Lab of Cognitive Neuroscience and Learning, Beijing Normal University, China;3. College of Information Science and Technology, Beijing Normal University, China |
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| Abstract: | The simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) recording technique has recently received considerable attention and has been used in many studies on cognition and neurological disease. EEG‐fMRI simultaneous recording has the advantage of enabling the monitoring of brain activity with both high temporal resolution and high spatial resolution in real time. The successful removal of the ballistocardiographic (BCG) artifact from the EEG signal recorded during an MRI is an important prerequisite for real‐time EEG‐fMRI joint analysis. We have developed a new framework dedicated to BCG artifact removal in real‐time. This framework includes a new real‐time R‐peak detection method combining a k‐Teager energy operator, a thresholding detector, and a correlation detector, as well as a real‐time BCG artifact reduction procedure combining average artifact template subtraction and a new multi‐channel referenced adaptive noise cancelling method. Our results demonstrate that this new framework is efficient in the real‐time removal of the BCG artifact. The multi‐channel adaptive noise cancellation (mANC) method performs better than the traditional ANC method in eliminating the BCG residual artifact. In addition, the computational speed of the mANC method fulfills the requirements of real‐time EEG‐fMRI analysis. © 2016 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 26, 209–215, 2016 |
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| Keywords: | EEG‐fMRI ballistocardiographic artifact real‐time k‐Teager energy operator adaptive noise cancelling |
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