Improving AR-SSVEP Recognition Accuracy Under High Ambient Brightness Through Iterative Learning-Reference-Cited by-同舟云学术

Improving AR-SSVEP Recognition Accuracy Under High Ambient Brightness Through Iterative Learning

Published:2023 Issue: Volume:31 Page:1796-1806
ISSN:1534-4320
Container-title:IEEE Transactions on Neural Systems and Rehabilitation Engineering
language:
Short-container-title:IEEE Trans. Neural Syst. Rehabil. Eng.

Author:

Zhang Rui¹^ORCID,Cao Lijun¹,Xu Zongxin¹^ORCID,Zhang Yangsong²,Zhang Lipeng¹^ORCID,Hu Yuxia¹,Chen Mingming¹^ORCID,Yao Dezhong¹^ORCID

Affiliation:

1. Henan Key Laboratory of Brain Science and Brain—Computer Interface Technology, School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, China

2. School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang, China

Funder

STI 2030-Major Project

Technology Project of Henan Province

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation

Link

http://xplorestaging.ieee.org/ielx7/7333/10031624/10078912.pdf?arnumber=10078912

Reference63 articles.

1. Towards BCI-Based Interfaces for Augmented Reality: Feasibility, Design and Evaluation

2. Assessing direction-specific adaptation using the steady-state visual evoked potential: Results from EEG source imaging

3. Current Challenges for the Practical Application of Electroencephalography-Based Brain–Computer Interfaces

4. Simultaneous Decoding of Eccentricity and Direction Information for a Single-Flicker SSVEP BCI

5. SSVEP Stimulus Layout Effect on Accuracy of Brain-Computer Interfaces in Augmented Reality Glasses

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