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Virtual Reality Game-Based Adaptive Neurofeedback Training for Motor Imagery

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12th Asian-Pacific Conference on Medical and Biological Engineering (APCMBE 2023)

Part of the book series: IFMBE Proceedings ((IFMBE,volume 103))

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Abstract

Motor imagery-based brain-computer interfaces (MI-BCIs) are promising tools for motor rehabilitation applications. However, neurofeedback training (NFT) of traditional MI is boring and takes a long time. This study aimed to investigate whether adaptive NFT in virtual reality (VR) scenes could improve MI-BCI performance. In this study, we proposed a VR game-based MI-BCI paradigm that contained left and right upper limbs MI tasks. In the course of training, the system could adaptively adjust the game difficulty and dynamic output decoding result according to the training performance of individuals. Six subjects participated in the experiments. After three days of NFT, the activation of the motor cortex was enhanced. The average accuracy of MI tasks reached 83.52%, with an increase of 10.46%, compared with before training. The results demonstrate that the adaptive NFT system based on VR games proposed in this study has a good effect on MI performance and is expected to be used in rehabilitation training and treatment for stroke.

Wang and Tian: These authors contributed equally to this work and should be considered co-first authors

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Acknowledgment

We express our sincere gratitude to all participants for their invaluable contributions to this study. Additionally, we acknowledge the support of STI 2030—Major Projects 2022ZD0208900, National Natural Science Foundation of China (62206198, 62122059, 81925020).

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Authors and Affiliations

  1. Academy of Medical Engineering and Translational Medicine, Tian** University, Tian**, China

    Kun Wang, Feifan Tian, Minpeng Xu, Bowen Dong & Dong Ming

  2. College of Precision Instruments and Optoelectronics Engineering, Tian** University, Tian**, China

    Lincong Pan, Minpeng Xu, Minglun Li & Dong Ming

Authors
  1. Kun Wang
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  2. Feifan Tian
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  3. Lincong Pan
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  4. Minpeng Xu
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  5. Minglun Li
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  6. Bowen Dong
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  7. Dong Ming
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Corresponding author

Correspondence to Minpeng Xu .

Editor information

Editors and Affiliations

  1. Department of Biomedical Engineering, School of Medicine, Tsinghua University, Bei**g, China

    Guangzhi Wang

  2. School of Life Science and Technology, University of Electronic Science and Technology, Chengdu, China

    Dezhong Yao

  3. State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nan**g, China

    Zhongze Gu

  4. Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine Peking Union Medical College, Bei**g, China

    Yi Peng

  5. School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China

    Shanbao Tong

  6. State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nan**g, China

    Chengyu Liu

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Wang, K. et al. (2024). Virtual Reality Game-Based Adaptive Neurofeedback Training for Motor Imagery. In: Wang, G., Yao, D., Gu, Z., Peng, Y., Tong, S., Liu, C. (eds) 12th Asian-Pacific Conference on Medical and Biological Engineering. APCMBE 2023. IFMBE Proceedings, vol 103. Springer, Cham. https://doi.org/10.1007/978-3-031-51455-5_33

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  • DOI: https://doi.org/10.1007/978-3-031-51455-5_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-51454-8

  • Online ISBN: 978-3-031-51455-5

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