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Updated: Jul 1, 2026

Assessment and Communication for People with Disorders of Consciousness
Published on: August 1, 2017
Brain-computer communication based on the dynamics of brain oscillations
G Pfurtscheller1, B Graimann, J E Huggins
1Department of Medical Informatics, Institute for Biomedical Engineering, Technical University of Graz, and Ludwig Boltzmann Institute for Medical Informatics and Neuroinformatics, Inffeldgasse 16a/II, A-8010 Graz, Austria. graimann@tugraz.at
This review explores brain-computer communication using motor imagery and brain oscillations. It details brain-switch technologies for controlling FES hand grasp in tetraplegics and discusses ECoG-based approaches.
Area of Science:
- Neuroscience
- Biomedical Engineering
- Rehabilitation Technology
Background:
- Brain-computer communication (BCC) offers novel interaction methods.
- Motor imagery (MI) and brain oscillations are key to decoding neural signals.
- Existing BCC systems face challenges in real-world application.
Purpose of the Study:
- To review brain-computer communication strategies utilizing motor imagery.
- To explore the dynamics of brain oscillations in BCC.
- To present novel brain-switch technologies for assistive applications.
Main Methods:
- Review of literature on motor imagery and brain oscillations for BCC.
- Explanation of BCC operational modes.
- Presentation of electroencephalography (EEG) and electrocorticography (ECoG) based brain-switch designs.
Main Results:
- Demonstration of an EEG-based brain switch controlling functional electrical stimulation (FES) for hand grasp.
- Presentation of an ECoG-based brain-switch approach.
- Analysis of motor imagery as a viable experimental strategy for BCC.
Conclusions:
- Brain-computer communication based on motor imagery shows significant promise for assistive technologies.
- EEG and ECoG offer distinct advantages for developing brain-switch interfaces.
- Further research can enhance control and applicability for individuals with severe motor impairments.
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