作者: Eunmok Yang , K Shankar , Eswaran Perumal , Changho Seo , None
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摘要: Brain-computer interface BCI) is a technology that assists in straight link among the human brain as well as external devices like computers or robotic systems, without including muscles and peripheral nerves. BCI allows individuals with motor disabilities to manage external devices with the aid of brain signals such as motor imagery detected from electroencephalography (EEG) signals. An EEG Motor Imagery Classification for BCI is a specific application of EEG in which brain signals directly related to motor imagery tasks are analyzed and classified to control external devices or applications, namely robotic systems or computers. In this regard, the study introduces a Jellyfish Optimization with Fuzzy Logic Enabled EEG Motor Imagery Classification for Brain Computer Interface (JFOFL-MICBCI) technique. The JFOFL-MICBCI technique aims to exploit the fuzzy logic system with metaheuristics for classifying EEC …