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Brain-machine interface (BMI) in paralysis.

U Chaudhary1, N Birbaumer2, M R Curado3

  • 1Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Germany.

Annals of Physical and Rehabilitation Medicine
|January 28, 2015
PubMed
Summary
This summary is machine-generated.

Non-invasive brain-machine interfaces (BMIs) offer new communication for ALS patients and aid motor recovery in stroke survivors. Functional near-infrared spectroscopy (fNIRS)-BMI enables communication for those with complete paralysis.

Keywords:
ALSAmyotrophic lateral sclerosisBCIBMIBrain computer interfaceBrain machine interfaceStroke

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Area of Science:

  • Neuroscience and Biomedical Engineering
  • Rehabilitation Medicine

Background:

  • Brain-machine interfaces (BMIs) enable paralyzed individuals to control external devices.
  • This review focuses on non-invasive BMIs for communication in amyotrophic lateral sclerosis (ALS) and motor recovery after stroke.

Purpose of the Study:

  • To review advances in non-invasive BMIs for communication in ALS patients.
  • To review advances in non-invasive BMIs for motor restoration in stroke patients.

Main Methods:

  • Electroencephalography (EEG) and near-infrared spectroscopy (NIRS) are key technologies for brain-computer interfaces.
  • Functional NIRS-BMI has been developed for communication in ALS patients with complete paralysis.
  • EEG-BMI and MEG-BMI are used for motor recovery studies in stroke patients due to their temporal resolution.

Main Results:

  • EEG-BMI enabled communication in ALS patients with residual eye control.
  • Functional NIRS-BMI facilitates communication in ALS patients with complete locked-in syndrome.
  • EEG-BMI training significantly improved motor performance in stroke patients with severe paresis.

Conclusions:

  • Non-invasive BMIs, particularly fNIRS-BMI, offer new communication avenues for severely paralyzed ALS patients.
  • BMI-based motor rehabilitation shows promise for improving motor function in stroke survivors.
  • Further research is needed to explore the neural basis and applications of BMI for motor restoration.