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Motor Imagery BCI-Based Online Control Soft Glove Rehabilitation System with Vibrotactile Stimulation

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Neural Information Processing (ICONIP 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1792))

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Abstract

Stroke patients often suffer from poor motor function recovery due to a lack of good rehabilitation training. And hand function impairments especially affect daily life. To enable stroke patients to perform rehabilitation training safely and effectively on their own, we have designed a soft pneumatic robotic system for application in active hand rehabilitation. The soft pneumatic glove in the system can safely lead passive movements with the hand. After training, the user can control the soft pneumatic glove to perform hand rehabilitation tasks by recognizing movement intentions through motor imagery brain-computer interface (MI-BCI). An experiment was designed to compare the rehabilitation performance of four healthy subjects under the visual-based rehabilitation task (VRT) and tactile-based rehabilitation task (TRT). Two subjects had improved online classification accuracy in TRT. Besides, the addition of the vibration stimuli resulted in stronger and long-lasting event-related desynchronization (ERD) than VRT in the sensorimotor cortex during the rehabilitation tasks. These results suggest that our hand rehabilitation system can effectively perform active rehabilitation tasks according to the user’s intention while ensuring safety and efficiency. The addition of vibration stimulation enhances cortical activation during the rehabilitation exercise, improving the efficiency and effectiveness of the rehabilitation. It also has the potential to improve the accuracy of the online classification of MI.

Supported by Basic Research Program of Jiangsu Province (BK201900240).

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Authors and Affiliations

  1. State Key Laboratory of Bioelectronics and Jiangsu Key Laboratory of Remote Measurement and Control, School of Instrument Science and Engineering, Southeast University, Nanjing, 210096, Jiangsu, China

    Wenbin Zhang, Aiguo Song & Jianwei Lai

Authors
  1. Wenbin Zhang
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  2. Aiguo Song
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  3. Jianwei Lai
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Corresponding author

Correspondence to Aiguo Song .

Editor information

Editors and Affiliations

  1. Indian Institute of Technology Indore, Indore, India

    Mohammad Tanveer

  2. Indian Institute of Information Technology - Allahabad, Prayagraj, India

    Sonali Agarwal

  3. Kobe University, Kobe, Japan

    Seiichi Ozawa

  4. Indian Institute of Technology Patna, Patna, India

    Asif Ekbal

  5. University of Innsbruck, Innsbruck, Austria

    Adam Jatowt

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Zhang, W., Song, A., Lai, J. (2023). Motor Imagery BCI-Based Online Control Soft Glove Rehabilitation System with Vibrotactile Stimulation. In: Tanveer, M., Agarwal, S., Ozawa, S., Ekbal, A., Jatowt, A. (eds) Neural Information Processing. ICONIP 2022. Communications in Computer and Information Science, vol 1792. Springer, Singapore. https://doi.org/10.1007/978-981-99-1642-9_39

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  • DOI: https://doi.org/10.1007/978-981-99-1642-9_39

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-1641-2

  • Online ISBN: 978-981-99-1642-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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