fNIRS Signal Classification Based on Deep Learning in Rock-Paper-Scissors Imagery Task
نویسندگان
چکیده
To explore whether the brain contains pattern differences in rock–paper–scissors (RPS) imagery task, this paper attempts to classify task using fNIRS and deep learning. In study, we designed an RPS with a total duration of 25 min 40 s, recruited 22 volunteers for experiment. We used acquisition device (FOIRE-3000) record cerebral neural activities these participants task. The time series classification (TSC) algorithm was introduced into time-domain signal classification. Experiments show that CNN-based TSC methods can achieve 97% accuracy method is suitable signals motor tasks, may find new application directions development brain–computer interfaces (BCI).
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ژورنال
عنوان ژورنال: Applied sciences
سال: 2021
ISSN: ['2076-3417']
DOI: https://doi.org/10.3390/app11114922