The application of EEG mental fatigue measurement based on Hilbert-Huang marginal spectrum

Kang Yu; Qing Tao; Runsheng Yin; Jingyao Fang; Di Wang

doi:10.1117/12.2636922

29 April 2022 The application of EEG mental fatigue measurement based on Hilbert-Huang marginal spectrum

Kang Yu, Qing Tao, Runsheng Yin, Jingyao Fang, Di Wang

Proceedings Volume 12247, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2022); 122471F (2022) https://doi.org/10.1117/12.2636922
Event: 2022 International Conference on Image, Signal Processing, and Pattern Recognition, 2022, Guilin, China

Abstract

Under the condition of modern information technology, the scale of battlefield electromagnetic information increases exponentially, which makes the electromagnetic environment more complex, and brings great opportunities and challenges to the development of anomaly detection algorithms in complex electromagnetic environment. Since the research in this field is still in its infancy and the research work system is not strong, this paper sorted out and analyzed relevant literatures at home and abroad, and sorted out and summarized traditional methods and deep learning methods respectively according to different anomaly detection algorithms. At the same time, the research difficulties and development trend of anomaly detection algorithm in complex electromagnetic environment are proposed to provide reference and suggestions for subsequent research.

Citation Download Citation

Kang Yu, Qing Tao, Runsheng Yin, Jingyao Fang, and Di Wang "The application of EEG mental fatigue measurement based on Hilbert-Huang marginal spectrum", Proc. SPIE 12247, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2022), 122471F (29 April 2022); https://doi.org/10.1117/12.2636922

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