Artifact subspace reconstruction

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Artifact subspace reconstruction
Abbreviations: ASR
Variations:
Category: Artifact subspace reconstruction
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Electroencephalogram analysis

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Artifact subspace reconstruction (ASR) is a processing step in EEG analysis. In the documentation to its reference implementation in EEGLAB Christian Kothe describes it by:

The basic principle is to first find a section of data that represents clean "reference" EEG and to compute statistics on there. Then, the function goes over the whole data in a sliding window and finds the subspaces in which there is activity that is more than a few standard deviations away from the reference EEG (this threshold is a tunable parameter). Once the function has found the bad subspaces it will treat them as missing data and reconstruct their content using a mixing matrix that was calculated on the clean data.

[edit] Method

  1. 1 minute callibration data
  2. Principal component analysis on a sliding window
  3. Remove high-variance PC components 3 standard deviations above the mean
  4. Reconstruct the signal with the remaining

[edit] Papers

  1. Real-time modeling and 3D visualization of source dynamics and connectivity using wearable EEG

[edit] External links

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