Article

Impairment of an individual's ability to communicate is a major hurdle for active
participation in education and social life. A lot of individuals with cerebral
palsy (CP) have normal intelligence, however, due to their inability to
communicate, they fall behind. Non-invasive electroencephalogram (EEG) based
brain-computer interfaces (BCIs) have been proposed as potential assistive
devices for individuals with CP. BCIs translate brain signals directly into
action. Motor activity is no longer required. However, translation of EEG signals
may be unreliable and requires months of training. Moreover, individuals with CP
may exhibit high levels of spontaneous and uncontrolled movement, which has a
large impact on EEG signal quality and results in incorrect translations. We
introduce a novel thought-based row-column scanning communication board that was
developed following user-centered design principles. Key features include an
automatic online artifact reduction method and an evidence accumulation procedure
for decision making. The latter allows robust decision making with unreliable BCI
input. Fourteen users with CP participated in a supporting online study and
helped to evaluate the performance of the developed system. Users were asked to
select target items with the row-column scanning communication board. The results
suggest that seven among eleven remaining users performed better than chance and
were consequently able to communicate by using the developed system. Three users
were excluded because of insufficient EEG signal quality. These results are very
encouraging and represent a good foundation for the development of real-world
BCI-based communication devices for users with CP.
CI - Copyright (c) 2015 Elsevier Masson SAS. All rights reserved.

Langue : ANGLAIS