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Editorial | Open Access

Evolving EEG signal processing techniques in the age of artificial intelligence

Li Hu1,2( )Zhiguo Zhang3( )
CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen 518000, Guangdong, China
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References

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ZJ Li, LB Zhang, FR Zhang, et al. Demystifying signal processing techniques to extract resting-state EEG responses for psychologists. Brain Sci Adv. 2020, 6(3): 189-209.
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LB Zhang, ZJ LI, FR Zhang, et al. Demystifying signal processing techniques to extract task-related EEG responses for psychologists. Brain Sci Adv. 2020, 6(3): 171-188.
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WR Hu, G Huang, LL Li, et al. Video-triggered EEG-emotion public databases and current methods: A survey. Brain Sci Adv. 2020, 6(3): 255-287.
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ZH Cao. A review of mainstreams of artificial intelligence for EEG-based brain-computer interfaces and their applications. Brain Sci Adv. 2020, 6(3): 162-170.
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WW Shi, JY Zhang, ZG Zhang, et al. An introduction and review on innovative silicon implementations of implanthe table/scalp EEG chips for data acquisition, seizure/behavior detection, and brain stimulation. Brain Sci Adv. 2020, 6(3): 242-254.
Brain Science Advances
Pages 159-161
Cite this article:
Hu L, Zhang Z. Evolving EEG signal processing techniques in the age of artificial intelligence. Brain Science Advances, 2020, 6(3): 159-161. https://doi.org/10.26599/BSA.2020.9050027

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Published: 04 February 2021
© The authors 2020

This article is published with open access at journals.sagepub.com/home/BSA

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