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Brain computer interface with the P300 speller: Usability for disabled people with amyotrophic lateral sclerosis

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TitleBrain computer interface with the P300 speller: Usability for disabled people with amyotrophic lateral sclerosis
Publication TypeJournal Article
AbstractObjectives: Amyotrophic lateral sclerosis (ALS), a progressive neurodegenerative disease, restricts patients’ communication capacity a few years after onset. A proof-of-concept of brain–computer interface (BCI) has shown promise in ALS and ‘‘locked-in’’ patients, mostly in pre-clinical studies or with only a few patients, but performance was estimated not high enough to support adoption by people with physical limitation of speech. Here, we evaluated a visual BCI device in a clinical study to determine whether disabled people with multiple deficiencies related to ALS would be able to use BCI to communicate in a daily environment. Methods: After clinical evaluation of physical, cognitive and language capacities, 20 patients with ALS were included. The P300 speller BCI system consisted of electroencephalography acquisition connected to real-time processing software and separate keyboard-display control software. It was equipped with original features such as optimal stopping of flashes and word prediction. The study consisted of two 3- block sessions (copy spelling, free spelling and free use) with the system in several modes of operation to evaluate its usability in terms of effectiveness, efficiency and satisfaction. Results: The system was effective in that all participants successfully achieved all spelling tasks and was efficient in that 65% of participants selected more than 95% of the correct symbols. The mean number of correct symbols selected per minute ranged from 3.6 (without word prediction) to 5.04 (with word prediction). Participants expressed satisfaction: the mean score was 8.7 on a 10-point visual analog scale assessing comfort, ease of use and utility. Patients quickly learned how to operate the system, which did not require much learning effort. Conclusion: With its word prediction and optimal stopping of flashes, which improves information transfer rate, the BCI system may be competitive with alternative communication systems such as eye- trackers. Remaining requirements to improve the device for suitable ergonomic use are in progress.
AuthorsGuy, V., Soriani M. - H., Bruno M., Papadopoulo T., Desnuelle C., and Clerc M.
Year of Publication2018
PublicationAnnals of Physical & Rehabilitation Medicine
Volume61
Pages5-11
ISSN1877-0657
Publisher DOIhttps://doi.org/10.1016/j.rehab.2017.09.004
Keywords (MeSH)adult, amyotrophic lateral sclerosis, brain-computer interfaces, research, software, technology
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