Medical & Biological Engineering & Computing

, Volume 45, Issue 5, pp 495–503

Removal of ocular artifacts from the EEG: a comparison between time-domain regression method and adaptive filtering method using simulated data

  • Ping He
  • Glenn Wilson
  • Christopher Russell
  • Maria Gerschutz
Original Article


We recently proposed an adaptive filtering (AF) method for removing ocular artifacts from EEG recordings. The method employs two parameters: the forgetting factor λ and the filter length M. In this paper, we first show that when λ = M = 1, the adaptive filtering method becomes equivalent to the widely used time-domain regression method. The role of λ (when less than one) is to deal with the possible non-stationary relationship between the reference EOG and the EOG component in the EEG. To demonstrate the role of M, a simulation study is carried out that quantitatively evaluates the accuracy of the adaptive filtering method under different conditions and comparing with the accuracy of the regression method. The results show that when there is a shape difference or a misalignment between the reference EOG and the EOG artifact in the EEG, the adaptive filtering method can be more accurate in recovering the true EEG by using an M larger than one (e.g. M = 2 or 3).


Adaptive filtering Electroencephalogram (EEG) Electro-oculogram (EOG) Noise canceling Regression method 


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Copyright information

© International Federation for Medical and Biological Engineering 2007

Authors and Affiliations

  • Ping He
    • 1
  • Glenn Wilson
    • 2
  • Christopher Russell
    • 2
  • Maria Gerschutz
    • 1
  1. 1.Department of Biomedical, Industrial and Human Factors EngineeringWright State UniversityDaytonUSA
  2. 2.Air Force Research LabWright-Patterson Air Force BaseDaytonUSA

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