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A P300 Brain-Computer Interface for Lower Limb Robot Control Based on Tactile Stimulation

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Abstract

Purpose

Tactile brain-computer interfaces can be used to express control intentions, avoiding motor imagery difficulties and visual fatigue. Tactile BCI has the problems of poor reproducibility and unclear features in applications. For further applications, a single-trial analysis of tactile-evoked P300 experiments is needed.

Methods

A brain-computer interface for single-trial analysis of vibrotactile stimulation-evoked P300 is proposed. It uses the combination of frequency and time period information as the feature extraction method and uses the maximum value of the most significant EEG channel as the input of the classifier to identify the control intention of the subject and use it to control the lower limb robot.

Results

The online experimental results show that online classification accuracy can reach 89.35 ± 4.86%, which realizes the closed loop of human neural motor rehabilitation. In addition, Subject 9, an elderly person, achieves an online accuracy rate of 83.33%.

Conclusion

A brain-computer interface based on the haptic-evoked P300 is developed and applied to control a lower limb rehabilitation robot. The classification results of an elderly individual verify the feasibility of the method.

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Acknowledgements

We thank all volunteers for their participation in the study. This work is supported by the Shanghai Science and Technology Innovation Action Plan (21S31902500) and grants from the S&T Program of Hebei (Grant Number 22375001D and 22372001D).

Author information

Authors and Affiliations

  1. School of Electrical Engineering, Hebei University of Technology, Tianjin, China

    Xiaoyu Duan & Mengge Wang

  2. School of Mechanical Engineering, Hebei University of Technology, Tianjin, China

    Shijie Guo

  3. School of Artificial Intelligence and Data Science, Hebei University of Technology, Tianjin, China

    Lingling Chen

  4. Intelligent Rehabilitation Device and Detection Technology Engineering Research Centre of the Ministry of Education, Tianjin, China

    Shijie Guo & Lingling Chen

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  1. Xiaoyu Duan
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Correspondence to Lingling Chen.

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Duan, X., Guo, S., Chen, L. et al. A P300 Brain-Computer Interface for Lower Limb Robot Control Based on Tactile Stimulation. J. Med. Biol. Eng. 43, 22–31 (2023). https://doi.org/10.1007/s40846-022-00766-9

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  • DOI: https://doi.org/10.1007/s40846-022-00766-9

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