Brain computer interface with EEG signals to improve feedback system in higher education based on augmentative and alternative communication
by Hua Sun; Hongxia Hou; Wenxia Song; Hongjuan Hu; Na Liu; Achyut Shankar
International Journal of Information and Communication Technology (IJICT), Vol. 24, No. 2, 2024

Abstract: A predictive brain-computer interface is a way to monitor EEG signals in humans currently under the experiment to understand the capability and get proper feedback about the digital education systems. The use of dynamically processed and collected data in a feedback system is unfeasible. Substantial processing delays are caused by a large volume of data utilised by the modern higher educational ideas. An artificial intelligence assisted brain-computer interface feedback system (AI-BCIFS) for augmentative and alternative communication is proposed to improve feedback analysis based on the EEG signals. AI-BCIFS method is proposed to avoid an unwanted and improper understanding of feedback in the higher education systems. An expanded optimisation methodology is introduced based on the feedback analysis, and the enhanced seeking feedback protocol (ESFP) has been developed to describe automatic recognition and storage. The experimental studies show that AI-BCIFAC is preferable to the existing approaches in terms of accuracy.

Online publication date: Tue, 05-Mar-2024

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