Host: Japan Society for Fuzzy Theory and Intelligent Informatics (SOFT)
This paper shows the result of the application of P300 speller to actual patients of ALS (amyotrophic lateral sclerosis). P300 speller, which uses P300 as the feature quantity and enables users to select letters just by thinking, is expected to be developed as a communication tool for seriously paralyzed patients like those with ALS. The aim of this study is to investigate the practicality of the actual application of the Japanese P300 speller to ALS subjects. In inputting letters with P300 speller, it is needed to input letters correctly in a short time to reduce user’s burden. It is also needed to do machine learning before use (pre-training). In the experiments, we applied RB-ARQ (Reliability-Based Automatic Repeat reQuest) and incremental learning method which the authors have been proposed. It is shown that discrimination speed can be improved with a small loss of the accuracy by applying RB-ARQ, which can reduce the number of stimuli to ALS subjects. This paper also shows that the incremental learning can reduce the pre-training time keeping the accuracy.
