Title :
Filtering of Muscle Artifact from the Electroencephalogram
Author :
Johnson, Timothy L. ; Wright, Stuart C. ; Segall, Adrian
Author_Institution :
Laboratory for Information and Decision Systems, Massachusetts Institute of Technology
Abstract :
When recorded by surface electrodes, the electroencephalogram (EEG) may contain unwanted signals due to depolarization of scalp muscles and various electrochemical effects at the surface-metal junction. The former artifacts, in particular, are difficult to remove by linear filtering. This design study indicates that a state-of-the-art non-linear filter which includes a matched-filter detector with likelihood-ratio decision logic can give significant performance improvement over a third-order linear low-pass filter typical of existing equipment. The same approach can be applied to related electrophysiological filtering problems.
Keywords :
Detectors; Electrodes; Electroencephalography; Filtering; Low pass filters; Matched filters; Maximum likelihood detection; Muscles; Nonlinear filters; Scalp; Biomedical Engineering; Electroencephalography; Electronics, Medical; Humans; Muscles; Neck; Scalp;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.1979.326443