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Subspace-based interference removal methods for a multichannel biomagnetic sensor array.

Kensuke Sekihara1, Srikantan S Nagarajan

  • 1Signal Analysis Inc., Hachioji, Tokyo, Japan. Department of Advanced Technology in Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8519, Japan.

Journal of Neural Engineering
|August 19, 2017
PubMed
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This study introduces a time-domain signal subspace for biomagnetic signal processing, offering a unified view of interference removal methods. This new perspective reveals underlying assumptions in techniques like adaptive noise canceling.

Area of Science:

  • Biomagnetic signal processing
  • Signal subspace theory
  • Time-domain analysis

Background:

  • Interfering magnetic fields pose challenges in biomagnetic signal processing.
  • Conventional signal subspace methods define subspaces in the spatial domain using lead field vectors.

Purpose of the Study:

  • To extend the concept of signal subspace into the time domain.
  • To provide a unified perspective on existing interference removal methods.

Main Methods:

  • Definition of a time-domain signal subspace based on source time courses.
  • Analysis of existing interference removal techniques through the lens of time-domain signal space projection.

Main Results:

  • The time-domain signal subspace exhibits symmetric relationships with the spatial-domain subspace.

Related Experiment Videos

  • Numerous interference removal methods, including adaptive noise canceling and spatio-temporal signal space separation, can be interpreted as time-domain signal space projections.
  • The differences between these methods stem from their approaches to defining the interference subspace.

    • Conclusions:

    • The time-domain signal subspace offers valuable insights into biomagnetic interference removal.
    • This framework unifies various existing techniques, highlighting their implicit assumptions and variations.