Motion artifact–controlled micro–brain sensors between hair follicles for persistent augmented reality brain–computer interfaces
Edited by John Rogers, Northwestern University–Evanston, Evanston, IL; received September 20, 2024; accepted March 8, 2025
Significance
This study overcomes traditional brain–computer interfaces’ (BCI) limitations by developing motion artifact–controlled micro–brain sensors that integrate seamlessly between hair strands. The sensor-integrated wearable system achieves ultralow impedance density and high-fidelity neural signal capture for multiple hours, even during intense motion, by demonstrating continuous telecommunication using augmented reality. This advance provides a pathway for the practical and continuous use of BCI in everyday life, enhancing the integration of digital and physical environments.
Abstract
Modern brain–computer interfaces (BCI), utilizing electroencephalograms for bidirectional human–machine communication, face significant limitations from movement-vulnerable rigid sensors, inconsistent skin–electrode impedance, and bulky electronics, diminishing the system’s continuous use and portability. Here, we introduce motion artifact–controlled micro–brain sensors between hair strands, enabling ultralow impedance density on skin contact for long-term usable, persistent BCI with augmented reality (AR). An array of low-profile microstructured electrodes with a highly conductive polymer is seamlessly inserted into the space between hair follicles, offering high-fidelity neural signal capture for up to 12 h while maintaining the lowest contact impedance density (0.03 kΩ·cm−2) among reported articles. Implemented wireless BCI, detecting steady-state visually evoked potentials, offers 96.4% accuracy in signal classification with a train-free algorithm even during the subject’s excessive motions, including standing, walking, and running. A demonstration captures this system’s capability, showing AR-based video calling with hands-free controls using brain signals, transforming digital communication. Collectively, this research highlights the pivotal role of integrated sensors and flexible electronics technology in advancing BCI’s applications for interactive digital environments.
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Data, Materials, and Software Availability
All study data are included in the article and/or supporting information.
Acknowledgments
We acknowledge the support from the NSF Research Traineeship (Grant No. NRT-FW-HTF 2345860) and the WISH Center grant from the Georgia Tech Institute for Matter and Systems. Electronic devices in this work were fabricated at the Institute for Matter and Systems, a member of the National Nanotechnology Coordinated Infrastructure, which is supported by the NSF (Grant No. ECCS-2025462). This research was partially supported by the Ministry of Trade, Industry, and Energy in Korea, under the Human Resource Development Program for Industrial Innovation (Global) (P0017303, Smart Manufacturing Global Talent Training Program) supervised by the Korea Institute for Advancement of Technology (KIAT). Some of this work was supported by a National Research Foundation of Korea grant funded by the Korean Government (Ministry of Science and Information and Communication Technology; RS-2023-NR076925). In addition, a part of this work was supported by the Institute of Information & Communications Technology Planning & Evaluation grant (RS-2024-00422098 and RS-2024-00443780) and the KIAT grant funded by the Korean government (MOTIE) (No. 2024-00435815) and Chungnam National University.
Author contributions
Hodam Kim, J.H.K., Y.J.L., T.J.K., and W.-H.Y. designed research; Hodam Kim, J.H.K., Y.J.L., H.H., S.C., S.B., H.L., C.-H.I., S.J.C., J.W.S., and W.-H.Y. performed research; Hodam Kim and J.H.K. contributed new reagents/analytic tools; Hodam Kim, J.H.K., J.L., H.Y., Hyeonseok Kim, Hojoong Kim, T.W.K., B.L., and W.-H.Y. analyzed data; and Hodam Kim, J.H.K., Y.J.L., K.J.Y., and W.-H.Y. wrote the paper.
Competing interests
Hodam Kim and W.-H.Y. are inventors on a pending patent application related to this work at Georgia Tech.
Supporting Information
Appendix 01 (PDF)
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Movie S1.
Demonstration of steady-state visual evoked potential monitoring while standing, walking, and running.
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Movie S2.
Demonstration of hands-free control of a video call system using steady-state visual evoked potential-based brain-computer interfaces.
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Movie S3.
Demonstration of the micro-sensor application on the human scalp.
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Copyright © 2025 the Author(s). Published by PNAS. This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).
Data, Materials, and Software Availability
All study data are included in the article and/or supporting information.
Submission history
Received: September 20, 2024
Accepted: March 8, 2025
Published online: April 7, 2025
Published in issue: April 15, 2025
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Acknowledgments
We acknowledge the support from the NSF Research Traineeship (Grant No. NRT-FW-HTF 2345860) and the WISH Center grant from the Georgia Tech Institute for Matter and Systems. Electronic devices in this work were fabricated at the Institute for Matter and Systems, a member of the National Nanotechnology Coordinated Infrastructure, which is supported by the NSF (Grant No. ECCS-2025462). This research was partially supported by the Ministry of Trade, Industry, and Energy in Korea, under the Human Resource Development Program for Industrial Innovation (Global) (P0017303, Smart Manufacturing Global Talent Training Program) supervised by the Korea Institute for Advancement of Technology (KIAT). Some of this work was supported by a National Research Foundation of Korea grant funded by the Korean Government (Ministry of Science and Information and Communication Technology; RS-2023-NR076925). In addition, a part of this work was supported by the Institute of Information & Communications Technology Planning & Evaluation grant (RS-2024-00422098 and RS-2024-00443780) and the KIAT grant funded by the Korean government (MOTIE) (No. 2024-00435815) and Chungnam National University.
Author contributions
Hodam Kim, J.H.K., Y.J.L., T.J.K., and W.-H.Y. designed research; Hodam Kim, J.H.K., Y.J.L., H.H., S.C., S.B., H.L., C.-H.I., S.J.C., J.W.S., and W.-H.Y. performed research; Hodam Kim and J.H.K. contributed new reagents/analytic tools; Hodam Kim, J.H.K., J.L., H.Y., Hyeonseok Kim, Hojoong Kim, T.W.K., B.L., and W.-H.Y. analyzed data; and Hodam Kim, J.H.K., Y.J.L., K.J.Y., and W.-H.Y. wrote the paper.
Competing interests
Hodam Kim and W.-H.Y. are inventors on a pending patent application related to this work at Georgia Tech.
Notes
This article is a PNAS Direct Submission.
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Motion artifact–controlled micro–brain sensors between hair follicles for persistent augmented reality brain–computer interfaces, Proc. Natl. Acad. Sci. U.S.A.
122 (15) e2419304122,
https://doi.org/10.1073/pnas.2419304122
(2025).
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