TY - GEN
T1 - Computer Artificial Intelligence Applied in the Judgement of Attentiveness Using EEG Signals Processing Technology
AU - Bu, Xiangeng
AU - Cao, Tianao
AU - Sun, Jinwei
AU - Wang, Qisong
AU - Liu, Dan
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/10/23
Y1 - 2021/10/23
N2 - The realization of intelligent education relies on the cross integration of artificial intelligence and the educational process, making education a traceable and visible process. This achieves the purpose of optimizing the teaching process and promoting learners to conduct personalized learning, thus creating an intelligent and technologically advanced learning environment. This paper collects the EEG signals of learners in learning process, and carries out the removal of noise and physiological artifact first, obtaining EEG signals with higher signal-to-noise ratio (SNR). To address the problem of subjective indicators of attentiveness evaluation, this paper extracts a variety of features (power spectral density, eSense index, and sample entropy), and makes a comprehensive comparison, so as to evaluate the state of attentiveness objectively.
AB - The realization of intelligent education relies on the cross integration of artificial intelligence and the educational process, making education a traceable and visible process. This achieves the purpose of optimizing the teaching process and promoting learners to conduct personalized learning, thus creating an intelligent and technologically advanced learning environment. This paper collects the EEG signals of learners in learning process, and carries out the removal of noise and physiological artifact first, obtaining EEG signals with higher signal-to-noise ratio (SNR). To address the problem of subjective indicators of attentiveness evaluation, this paper extracts a variety of features (power spectral density, eSense index, and sample entropy), and makes a comprehensive comparison, so as to evaluate the state of attentiveness objectively.
KW - EEG signals
KW - PSD
KW - attentiveness
KW - eSense index
KW - sample entropy
UR - https://www.scopus.com/pages/publications/85126661514
U2 - 10.1145/3495018.3501122
DO - 10.1145/3495018.3501122
M3 - 会议稿件
AN - SCOPUS:85126661514
T3 - ACM International Conference Proceeding Series
SP - 2462
EP - 2468
BT - Proceedings of 2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture, AIAM 2021
PB - Association for Computing Machinery
T2 - 3rd International Conference on Artificial Intelligence and Advanced Manufacture, AIAM 2021
Y2 - 23 October 2021 through 25 October 2021
ER -