  Objective: Amyotrophic lateral sclerosis (ALS) is a rare disease, but is also
one of the most common motor neuron diseases, and people of all races and
ethnic backgrounds are affected. There is currently no cure. Brain computer
interfaces (BCIs) can establish a communication channel directly between the
brain and an external device by recognizing brain activities that reflect user
intent. Therefore, this technology could help ALS patients in promoting
functional independence through BCI-based speller systems and motor assistive
devices. Methods: In this paper, two kinds of ERP-based speller systems were
tested on 18 ALS patients to: (1) assess performance when they spelled 42
characters online continuously, without a break; and (2) to compare performance
between a matrix-based speller paradigm (MS-P, mean visual angle 6 degree) and
a new speller paradigm that used a larger visual angle called the large visual
angle speller paradigm (LS-P, mean visual angle 8 degree). Results: Although
results showed that there were no significant differences between the two
paradigms in accuracy trend over continuous use (p>0.05), the fatigue during
the LS-P condition was significantly lower than that of MS-P (p<0.05). Results
also showed that continuous use slightly reduced the performance of this
ERP-based BCI. Conclusion: 15 subjects obtained higher than 80% feedback
accuracy (online output accuracy) and 9 subjects obtained higher than 90%
feedback accuracy in one of the two paradigms, thus validating the BCI
approaches in this study. Significance: Most ALS subjects in this study could
spell effectively after continuous use of an ERP-based BCI. The new LS-P
display may be easier for subjects to use, resulting in lower fatigue.
