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BCIs using motor imagery and sensorimotor rhythms

BCIs using motor imagery and sensorimotor rhythms

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Motor imagery (MI) Brain Computer Interfaces (BCI) are considered the most prominent paradigms of endogenous BCIs, as they comply with the requirements of asynchronous implementations. As MI BCIs can be operated via the movement imagination of one limb (e.g., left hand), after a training period, the user can harness such an interface without the aid of external cue(s) that are considered ideal for self-paced implementations. MI BCIs have been employed in several cases as a means of both communication restoration and neurorehabilitation. Neuromuscular disease (NMD), although rarely studied within the context of MI BCIs, presents significant interest mainly due to the disease's progressive nature and the impact it has on each patient's brain reorganization.

Chapter Contents:

  • 9.1 Introduction to sensorimotor rhythm (SMR)
  • 9.2 Common processing practices
  • 9.3 MI BCIs for patients with motor disabilities
  • 9.3.1 MI BCIs for patients with sudden loss of motor functions
  • 9.3.2 MI BCIs for patients with gradual loss of motor functions
  • 9.4 MI BCIs for NMD patients
  • 9.4.1 Condition description
  • 9.4.2 Experimental design
  • Participants
  • Experimental environment
  • Experimental design
  • Preprocessing
  • PLV measurements and functional connectivity patterns
  • Network metrics
  • Time-indexed patterns of functional connectivity
  • Feature screening
  • SVM classifiers as MI-direction decoders
  • Group analysis of pairwise couplings
  • Group analysis of network metrics
  • Personalized MI decoding—SVM classification based on static patterns
  • Personalized MI decoding—SVM classification based on time-varying patterns
  • 9.5 Toward a self-paced implementation
  • 9.5.1 Related work
  • 9.5.2 An SVM-ensemble for self-paced MI decoding
  • 9.5.3 In quest of self-paced MI decoding
  • 9.6 Summary
  • References

Inspec keywords: neurophysiology; medical signal processing; brain-computer interfaces; electroencephalography; diseases; patient rehabilitation; brain

Other keywords: sensorimotor rhythms; self-paced implementations; Motor imagery Brain Computer Interfaces; asynchronous implementations; endogenous BCIs; MI BCIs; prominent paradigms

Subjects: Electrical activity in neurophysiological processes; Bioelectric signals; Signal processing and detection; Electrodiagnostics and other electrical measurement techniques; Biophysics of neurophysiological processes; Patient diagnostic methods and instrumentation; Biology and medical computing; User interfaces; Patient care and treatment; Digital signal processing

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