4.5 Article

Non-invasive brain-computer interface system: Towards its application as assistive technology

Journal

BRAIN RESEARCH BULLETIN
Volume 75, Issue 6, Pages 796-803

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.brainresbull.2008.01.007

Keywords

EEG-based brain-computer interfaces; assistive robotics; severe motor impairment; technologies for independent life

Categories

Funding

  1. NIBIB NIH HHS [R01 EB006356-01, EB006356, EB00856, R01 EB000856, R01 EB006356, R01 EB000856-01] Funding Source: Medline
  2. NICHD NIH HHS [R01 HD030146, HD30146] Funding Source: Medline
  3. Telethon [GUP03562] Funding Source: Medline

Ask authors/readers for more resources

The quality of life of people suffering from severe motor disabilities can benefit from the use of current assistive technology capable of ameliorating communication, house-environment management and mobility, according to the user's residual motor abilities. Brain-computer interfaces (BCIs) are systems that can translate brain activity into signals that control external devices. Thus they can represent the only technology for severely paralyzed patients to increase or maintain their communication and control options. Here we report on a pilot study in which a system was implemented and validated to allow disabled persons to improve or recover their mobility (directly or by emulation) and communication within the surrounding environment. The system is based on a software controller that offers to the user a communication inter-face that is matched with the individual's residual motor abilities. Patients (n = 14) with severe motor disabilities due to progressive neurodegenerative disorders were trained to use the system prototype under a rehabilitation program carried out in a house-like furnished space. All users utilized regular assistive control options (e.g., microswitches or head trackers). In addition, four subjects learned to operate the system by means of a non-invasive EEG-based BCI. This system was controlled by the subjects' voluntary modulations of EEG sensorimotor rhythms recorded on the scalp; this skill was learnt even though the subjects have not had control over their limbs for a long time. We conclude that such a prototype system, which integrates several different assistive technologies includina a BCI system, can potentially facilitate the translation from pre-clinical demonstrations to a clinical useful BCI. (c) 2008 Elsevier Inc. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available