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Conformal in-ear bioelectronics for visual and auditory brain-computer interfaces

Author

Listed:
  • Zhouheng Wang

    (Tsinghua University
    Tsinghua University)

  • Nanlin Shi

    (Tsinghua University)

  • Yingchao Zhang

    (Tsinghua University)

  • Ning Zheng

    (Zhejiang University)

  • Haicheng Li

    (Tsinghua University
    Tsinghua University)

  • Yang Jiao

    (Tsinghua University
    Tsinghua University)

  • Jiahui Cheng

    (Tsinghua University
    Tsinghua University)

  • Yutong Wang

    (Tsinghua University
    Tsinghua University)

  • Xiaoqing Zhang

    (Capital Medical University)

  • Ying Chen

    (Institute of Flexible Electronics Technology of THU)

  • Yihao Chen

    (Tsinghua University
    Tsinghua University)

  • Heling Wang

    (Tsinghua University
    Tsinghua University)

  • Tao Xie

    (Zhejiang University)

  • Yijun Wang

    (Chinese Academy of Sciences)

  • Yinji Ma

    (Tsinghua University
    Tsinghua University)

  • Xiaorong Gao

    (Tsinghua University)

  • Xue Feng

    (Tsinghua University
    Tsinghua University)

Abstract

Brain-computer interfaces (BCIs) have attracted considerable attention in motor and language rehabilitation. Most devices use cap-based non-invasive, headband-based commercial products or microneedle-based invasive approaches, which are constrained for inconvenience, limited applications, inflammation risks and even irreversible damage to soft tissues. Here, we propose in-ear visual and auditory BCIs based on in-ear bioelectronics, named as SpiralE, which can adaptively expand and spiral along the auditory meatus under electrothermal actuation to ensure conformal contact. Participants achieve offline accuracies of 95% in 9-target steady state visual evoked potential (SSVEP) BCI classification and type target phrases successfully in a calibration-free 40-target online SSVEP speller experiment. Interestingly, in-ear SSVEPs exhibit significant 2nd harmonic tendencies, indicating that in-ear sensing may be complementary for studying harmonic spatial distributions in SSVEP studies. Moreover, natural speech auditory classification accuracy can reach 84% in cocktail party experiments. The SpiralE provides innovative concepts for designing 3D flexible bioelectronics and assists the development of biomedical engineering and neural monitoring.

Suggested Citation

  • Zhouheng Wang & Nanlin Shi & Yingchao Zhang & Ning Zheng & Haicheng Li & Yang Jiao & Jiahui Cheng & Yutong Wang & Xiaoqing Zhang & Ying Chen & Yihao Chen & Heling Wang & Tao Xie & Yijun Wang & Yinji M, 2023. "Conformal in-ear bioelectronics for visual and auditory brain-computer interfaces," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39814-6
    DOI: 10.1038/s41467-023-39814-6
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    References listed on IDEAS

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