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Human factors engineering of BCI: an evaluation for satisfaction of BCI based on motor imagery

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Abstract

Existing brain-computer interface (BCI) research has made great progress in improving the accuracy and information transfer rate (ITR) of BCI systems. However, the practicability of BCI is still difficult to achieve. One of the important reasons for this difficulty is that human factors are not fully considered in the research and development of BCI. As a result, BCI systems have not yet reached users’ expectations. In this study, we investigate a BCI system of motor imagery for lower limb synchronous rehabilitation as an example. From the perspective of human factors engineering of BCI, a comprehensive evaluation method of BCI system development is proposed based on the concept of human-centered design and evaluation. Subjects’ satisfaction ratings for BCI sensors, visual analog scale (VAS), subjects’ satisfaction rating of the BCI system, and the mental workload rating for subjects manipulating the BCI system, as well as interview/follow-up comprehensive evaluation of motor imagery of BCI (MI-BCI) system satisfaction were used. The methods and concepts proposed in this study provide useful insights for the design of personalized MI-BCI. We expect that the human factors engineering of BCI could be applied to the design and satisfaction evaluation of MI-BCI, so as to promote the practical application of this kind of BCI.

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Data availability

The data used to support the findings of this study are included in this article, and the corresponding authors can be contacted for further inquiries.

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Funding

This study was supported by the National Natural Science Foundation of China (81771926, 61763022, 81470084, 61463024, 62006246, 82172058).

Author information

Authors and Affiliations

  1. Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, Yunnan, China

    Xiaotong Lyu, Peng Ding, Siyu Li, Yuyang Dong, Lei Su & Yunfa Fu

  2. Brain Cognition and Brain-Computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming, Yunnan, China

    Xiaotong Lyu, Peng Ding, Siyu Li, Yuyang Dong & Yunfa Fu

  3. School of Information Engineering, Chinese People’s Armed Police Force Engineering University, Xian, Shanxi, China

    Anmin Gong

  4. Faculty of Science, Kunming University of Science and Technology, Kunming, Yunnan, China

    Lei Zhao

Authors
  1. Xiaotong Lyu
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  2. Peng Ding
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  3. Siyu Li
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  4. Yuyang Dong
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  5. Lei Su
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  6. Lei Zhao
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  7. Anmin Gong
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  8. Yunfa Fu
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Contributions

XL: experimental design, data collection and analysis, experimental results visualization and paper writing; SL and YD: data curation and analysis; PD and AG: review and revision of the paper; LS: supervision and guidance; LZ: Experimental design validation and verification; YF: Funding support and paper revision. All authors have made significant contributions to the submission and have agreed to the final version of the manuscript.

Corresponding author

Correspondence to Yunfa Fu.

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All authors of this article declare that there is no conflict of interest.

Ethical statement

The studies involving human participants were reviewed and approved by Medical Ethics Committee of Kunming University of Science and Technology School of Medicine. The research was conducted in accordance with the principles embodied in the Declaration of Helsinki and in accordance with local statutory requirements. All participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individuals for the publication of any potentially identifiable images or data included in this article.

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Lyu, X., Ding, P., Li, S. et al. Human factors engineering of BCI: an evaluation for satisfaction of BCI based on motor imagery. Cogn Neurodyn 17, 105–118 (2023). https://doi.org/10.1007/s11571-022-09808-z

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  • DOI: https://doi.org/10.1007/s11571-022-09808-z

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