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A Brain-Computer Interface (BCI) offers a communication option to those who suffer from amyotrophic lateral sclerosis (ALS) and other motor disabilities. The majority of BCIs use a visual interface. Visual paradigms offer the highest communication rates when compared to other modalities such as auditory or tactile. One of the greatest challenges in BCI is signal-to-noise ratio (SNR). There is substantial research in signal processing to improve classification techniques and SNR. However, past research in visual attention has been largely overlooked and could improve SNR and usability. This work will review the present BCI paradigms and examine them under visual attention principles. The original visual paradigm, Row/Column (RC), was developed as a fast and simple method to present all of the items of a matrix rapidly. The RC paradigm design did not consider visual attention research topics such as; Gestalt grouping, attentional blink, flanker effects, and space based attention. Attentional principles can explain errors in BCI paradigms (adjacency error, attentional blink, non-target distraction) and how other paradigms have improved performance over RC. In addition, researchers use event-related potential components associated with different types of perception such as motion onset, covert attention, and color processing in an attempt to improve classification. By combining visual attention and signal processing research, a more effective BCI that is easier to use can be brought to those to need it most.

Brain-Computer Interface is an alternative method of communication. Amyotrophic lateral sclerosis (ALS) patients can derive benefit from BCI use, as ALS can result in locked-in syndrome. The present BCI operates via event- related potentials (ERPs) extracted from the EEG. Items (i.e., alphanumeric characters and keyboard commands) attended to by the subject should produce a P300 ERP; unattended items should not. Stepwise linear discriminant analysis is used to classify the items as attended or unattended. Many studies show that ALS patients can communicate using the P300 BCI; however, no study has systematically examined BCI performance longitudinally. This study examines the relationship between disease progression, BCI performance, and several other factors. Nine patients are enrolled in the study and data are collected in intervals of eight weeks. In each session, the ALSFRS-r is administered to track disease progression, followed by four EEG tasks: resting EEG, a cognitive task, an oddball task, and a copy spelling task. The oddball task generated a P300 for attended stimuli, and not for unattended stimuli. ALSFRS-r scores have decreased by 2.8 points on average, mean BCI copy spelling accuracy is 94.4%. Overall, the results suggest that BCI performance remains stable as disease progression continues.

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No description available.

No description available.

No description available.

No description available.