Tuesday, November 29, 2011

Can We Use Computers For Brain Rehabilitation?

 Seeking to improve neurorehabilitation, European scientists developed new systems of brain-computer interface.

Stroke is one of the leading causes of movement disability worldwide with patients never regaining full control of upper limbs. Brain-computer interface (BCI) is a revolutionary technology that allows severely disabled patients to convey brain signals through an external device providing a new communication channel between the brain and a computer.


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Thanks to the cortical plasticity of the brain, signals from implanted prostheses can, after adaptation, be handled by the brain like natural sensor channels. Mental activity involves electrical activity, and these electrophysiological signals can be detected with techniques like the Electroencephalogram (EEG) or Electrocorticogram (ECoG). The BCI system detects such changes and transforms them into control signals. Although advanced signal processing methods are used in BCI research, the output of a BCI is still unreliable. Furthermore, the information transfer rates are very low compared with conventional human interaction interfaces.

The main objective of the EU-funded ‘Neurorehabilitation using brain-computer interface’ (Rehabci) project was to analyse the possibility of using various non-invasive BCI approaches for movement rehabilitation in patients with severe motor disabilities. By collaborating with industry, researchers exploited the learning skills of the users to compensate the unreliability of the BCI system. They developed a non-invasive BCI system that used steady-state visual evoked potentials (SSVEP) which represent elicited exogenous responses of the patient’s brain under visual stimulations at specific frequencies. Prior to being tested on patients, the efficacy and accuracy of this system was evaluated in healthy subjects.

The BCI system developed by the Rehabci project is expected to foster progress in neurophysiology and other related disciplines. The application of this new BCI technology for communication and robotics will significantly aid patient recovery from severe motor disability.


Contacts and sources:
CORDIS Features
Ms. Silke Reinold,
Universitaet Bremen
Result from the EU funded FP7-PEOPLE programme
 

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