title: Ballistocardiogram artifact removal with a reference layer and standard EEG cap.
abstract: BACKGROUND
  In simultaneous EEG-fMRI, the EEG recordings are severely contaminated by ballistocardiogram (BCG) artifacts, which are caused by cardiac pulsations. To reconstruct and remove the BCG artifacts, one promising method is to measure the artifacts in the absence of EEG signal by placing a group of electrodes (BCG electrodes) on a conductive layer (reference layer) insulated from the scalp. However, current BCG reference layer (BRL) methods either use a customized EEG cap composed of electrode pairs, or need to construct the custom reference layer through additional model-building experiments for each EEG-fMRI experiment. These requirements have limited the versatility and efficiency of BRL. The aim of this study is to propose a more practical and efficient BRL method and compare its performance with the most popular BCG removal method, the optimal basis sets (OBS) algorithm.
  
  
  METHODS
  By designing the reference layer as a permanent and reusable cap, the new BRL method is able to be used with a standard EEG cap, and no extra experiments and preparations are needed to use the BRL in an EEG-fMRI experiment.
  
  
  RESULTS
  The BRL method effectively removed the BCG artifacts from both oscillatory and evoked potential scalp recordings and recovered the EEG signal.
  
  
  CONCLUSIONS
  Compared to the OBS, this new BRL method improved the contrast-to-noise ratios of the alpha-wave, visual, and auditory evoked potential signals by 101%, 76%, and 75%, respectively, employing 160 BCG electrodes. Using only 20 BCG electrodes, the BRL improved the EEG signal by 74%/26%/41%, respectively.
  
  
  CONCLUSIONS
  The proposed method can substantially improve the EEG signal quality compared with traditional methods.
authors: Department of Radiology, Stanford University, Stanford, CA 94305, USA. Electronic address: qfluo@stanford.edu.
authors: Qingfei
authors: Q
authors: Luo
authors: Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China.
authors: Xiaoshan
authors: X
authors: Huang
authors: Department of Radiology, Stanford University, Stanford, CA 94305, USA.
authors: Gary H
authors: GH
authors: Glover
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D016477:Artifacts; D001450:Ballistocardiography / Q000379:methods*; D001921:Brain / Q000502:physiology; D004566:Electrodes; D004569:Electroencephalography / Q000295:instrumentation / Q000379:methods*; D005071:Evoked Potentials; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D064847:Multimodal Imaging / Q000295:instrumentation / Q000379:methods; D010507:Periodicity; D017156:Photoplethysmography / Q000379:methods; D012815:Signal Processing, Computer-Assisted; D055815:Young Adult
keywords: BCG artifact; Ballistocardiogram; EEG-fMRI; OBS; Reference layer; Removal