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An ERP-based BCI with peripheral stimuli: validation with ALS patients

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Abstract

Many studies reported that ERP-based BCIs can provide communication for some people with amyotrophic lateral sclerosis (ALS). ERP-based BCIs often present characters within a matrix that occupies the center of the visual field. However, several studies have identified some concerns with the matrix-based approach. This approach may lead to fatigue and errors resulting from flashing adjacent stimuli, and is impractical for users who might want to use the BCI in tandem with other software or feedback in the center of the monitor. In this paper, we introduce and validate an alternate ERP-based BCI display approach. By presenting stimuli near the periphery of the display, we reduce the adjacency problem and leave the center of the display available for feedback or other applications. Two ERP-based display approaches were tested on 18 ALS patients to: (1) compare performance between a conventional matrix speller paradigm (Matrix-P, mean visual angle 6°) and a new speller paradigm with peripherally distributed stimuli (Peripheral-P, mean visual angle 8.8°); and (2) assess performance while spelling 42 characters online continuously, without a break. In the Peripheral-P condition, 12 subjects attained higher than 80% feedback accuracy during online performance, and 7 of these subjects obtained higher than 90% accuracy. The experimental results showed that the Peripheral-P condition yielded performance comparable to the conventional Matrix-P condition (p > 0.05) in accuracy and information transfer rate. This paper introduces a new display approach that leaves the center of the monitor open for feedback and/or other display elements, such as movies, games, art, or displays from other AAC software or conventional software tools.

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Acknowledgements

This work was supported by the National key research and development program 2017YFB13003002. This work was also supported in part by the Grant National Natural Science Foundation of China, under Grant Nos. 61573142, 61773164 and 91420302, and the programme of Introducing Talents of Discipline to Universities (the 111 Project) under Grant B17017.

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  1. Yangyang Miao and Erwei Yin are contributed equally to this work.

Authors and Affiliations

  1. Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, People’s Republic of China

    Yangyang Miao, Xingyu Wang & Jing Jin

  2. Unmanned Systems Research Center, National Institute of Defense Technology Innovation, Academy of Military Sciences China, Beijing, 100071, People’s Republic of China

    Erwei Yin

  3. Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin, 300450, People’s Republic of China

    Erwei Yin

  4. Department of Cognitive Science, University of California at San Diego, La Jolla, San Diego, CA, USA

    Brendan Z. Allison

  5. Department of Psychiatry and Behavior Sciences, Stanford University, Stanford, CA, 94305, USA

    Yu Zhang

  6. Department of Neurology, Huashan Hospital, Fudan University, Shanghai, People’s Republic of China

    Yan Chen & Yi Dong

  7. College of Mechatronic Engineering and Automation, National University of Defense Technology Changsha, Hunan, 410073, People’s Republic of China

    Dewen Hu

  8. Skolkowo Institute of Science and Technology (SKOLTECH), Moscow, Russia, 143026

    Andrzej Chchocki

  9. Systems Research Institute PAS, Warsaw, Poland

    Andrzej Chchocki

  10. Nicolaus Copernicus University (UMK), Torun, Poland

    Andrzej Chchocki

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  1. Yangyang Miao
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  4. Yu Zhang
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Correspondence to Yan Chen or Jing Jin.

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Miao, Y., Yin, E., Allison, B.Z. et al. An ERP-based BCI with peripheral stimuli: validation with ALS patients. Cogn Neurodyn 14, 21–33 (2020). https://doi.org/10.1007/s11571-019-09541-0

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