Robust EEG signal processing with signal structures

Robust EEG signal processing with signal structures

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Brain decoding has contributed to the development of cognitive neuroscience and the production of brain-machine interfaces/brain-computer interfaces (BCI/BMI). For brain decoding, electroencephalography (EEG), which allows the observation of the electrophysiological activities of neurons, is widely used to observe brain activity. In particular, an EEG read from electrodes installed on a scalp, which has some advantages when it comes to cost, size, and ease of measurement, is a promising recording method for producing noninvasive BMIs against magnetoencephalograms, functional magnetic resonance imaging, and so on. However, an EEG signal has low spatial resolution and is highly affected by noise. Moreover, the recoding of an EEG is time-consuming and tires BMI users. Therefore, signal processing techniques that can robustly extract brain activity patterns from EEG signals with a low signal-to-noise ratio and a small sample size are necessary. One approach to achieve such techniques is to incorporate additional information retrieved separately from an EEG in signal processing. This chapter describes some techniques that can accomplish this. The signal structures include physical structures, such as the location of the electrodes, and functional structures, such as synchronizing brain regions. The discussion on the importance of the signal structures in a source analysis of EEG signals that can improve the BMI performance will be discussed in this chapter. In contrast to a source analysis, which finds the brain patterns in a source domain, regularization incorporating the signal structures in a sensor domain will be discussed. Moreover, we will show the signal processing in a graph spectral domain that is a vector space derived from the signal structure.

Chapter Contents:

  • Abstract
  • 4.1 Introduction
  • 4.2 Source analysis
  • 4.3 Regularization
  • 4.4 Filtering in graph spectral domain
  • 4.4.1 Graph Fourier transform
  • 4.4.2 Smoothing and dimensionality reduction by GFT
  • 4.4.3 Tangent space mapping from Riemannian manifold
  • 4.4.4 Smoothing on functional brain structures
  • 4.5 Conclusion
  • References

Inspec keywords: electroencephalography; biomedical electrodes; medical signal processing; neurophysiology; brain-computer interfaces

Other keywords: electrodes; electroencephalography; BCI-BMI; EEG signal; brain activity patterns; signal processing; brain regions; brain patterns; signal structure; neuron electrophysiological activities; brain-machine interfaces-brain-computer interfaces; brain decoding; functional magnetic resonance imaging; magnetoencephalograms

Subjects: Electrical activity in neurophysiological processes; Biology and medical computing; User interfaces; Electrodiagnostics and other electrical measurement techniques; Signal processing and detection; Digital signal processing; Bioelectric signals

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