Scholarly Research Excellence
@article{(International Science Index):,
  title    = {Removing Ocular Artifacts from EEG Signals using Adaptive Filtering and ARMAX Modeling},
  author    = {Parisa Shooshtari and  Gelareh Mohamadi and  Behnam Molaee Ardekani and  Mohammad Bagher Shamsollahi},
  country   = {},
  abstract  = {EEG signal is one of the oldest measures of brain
activity that has been used vastly for clinical diagnoses and
biomedical researches. However, EEG signals are highly
contaminated with various artifacts, both from the subject and from
equipment interferences. Among these various kinds of artifacts,
ocular noise is the most important one. Since many applications such
as BCI require online and real-time processing of EEG signal, it is
ideal if the removal of artifacts is performed in an online fashion.
Recently, some methods for online ocular artifact removing have
been proposed. One of these methods is ARMAX modeling of EEG
signal. This method assumes that the recorded EEG signal is a
combination of EOG artifacts and the background EEG. Then the
background EEG is estimated via estimation of ARMAX parameters.
The other recently proposed method is based on adaptive filtering.
This method uses EOG signal as the reference input and subtracts
EOG artifacts from recorded EEG signals. In this paper we
investigate the efficiency of each method for removing of EOG
artifacts. A comparison is made between these two methods. Our
undertaken conclusion from this comparison is that adaptive filtering
method has better results compared with the results achieved by
ARMAX modeling.},
    journal   = {International Journal of Medical, Health, Biomedical, Bioengineering and Pharmaceutical Engineering},  volume    = {1},
  number    = {11},
  year      = {2007},
  pages     = {617 - 620},
  ee        = {},
  url       = {},
  bibsource = {},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 11, 2007},