Highly stretchable, hair-compatible multichannel neural interface with time-stable hydrogel for high-fidelity long-term EEG sensing.
Overview
- Department of Biomedical Engineering, Cockrell School of Engineering, The University of Texas at Austin, Austin, TX 78712, USA
- Chandra Department of Electrical and Computer Engineering, Cockrell School of Engineering, The University of Texas at Austin, Austin, TX 78712, USA
- Department of Neurology, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA
- Mulva Clinic for the Neurosciences, The University of Texas at Austin, Austin, TX 78712, USA
Abstract
Reliable brain-computer interfaces (BCIs) require electroencephalography (EEG) sensors that maintain conformal, low-impedance contact through hair, motion, and repeated use. Here, we present MindStretcH, a stretchable and hair-compatible EEG platform integrating a kirigami-patterned elastomeric mesh, deformable eutectic gallium-indium (EGaIn) interconnects, and detachable hydrogel-based conical electrodes. The system adapts to variations in head geometry, preserves electrical performance under substantial mechanical deformation, and maintains stable electrode-scalp contact over prolonged use. Longitudinal motor-imagery recordings and repeated online BCI experiments showed consistent task-related EEG activity without measurable deterioration in recording quality. These results establish MindStretcH as a reusable platform for long-term EEG monitoring and BCI applications in laboratory, clinical, and home settings.
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Zenodo 19422275
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Version 1, 6 October 2026: the first record
Recorded: type, language, journal, volume, issue, pages, dates, 19 authors, 6 MeSH terms, 11 funders, 41 references.
Cite
This paper
Hsieh, J.-C., Yao, M., Alawieh, H., Koptelova, V., Kumar, S., Tang, K. W. K., Wang, W., Jeong, J., Ding, H., Ahmad, Z., Wang, D., Engrav, T., Wang, R., Gupta, A., He, W., Moscoso-Barrera, W. D., Grimes, A., Millán, J. d. R., & Wang, H. (2026). Highly stretchable, hair-compatible multichannel neural interface with time-stable hydrogel for high-fidelity long-term EEG sensing. Science advances, 12(40), eaee1540. https://
BibTeX
@article{hsieh2026highly
author = {Hsieh, Ju-Chun and Yao, Mengmeng and Alawieh, Hussein and Koptelova, Victoria and Kumar, Satyam and Tang, Kai Wing Kevin and Wang, Wenliang and Jeong, Jinmo and Ding, Hong and Ahmad, Zoya and Wang, Derek and Engrav, Tlali and Wang, Reyna and Gupta, Ashwin and He, Weilong and Moscoso-Barrera, William D. and Grimes, Ayden and Millán, José del R. and Wang, Huiliang},
title = {{Highly stretchable, hair-compatible multichannel neural interface with time-stable hydrogel for high-fidelity long-term EEG sensing}},
journal = {Science advances},
year = {2026},
month = oct,
volume = {12},
number = {40},
pages = {eaee1540},
publisher = {American Association for the Advancement of Science},
issn = {2375-2548},
doi = {10.1126/
url = {https://
pmid = {42826206},
pmcid = {PMC13632756}
}
RIS
TY - JOUR
AU - Hsieh, Ju-Chun
AU - Yao, Mengmeng
AU - Alawieh, Hussein
AU - Koptelova, Victoria
AU - Kumar, Satyam
AU - Tang, Kai Wing Kevin
AU - Wang, Wenliang
AU - Jeong, Jinmo
AU - Ding, Hong
AU - Ahmad, Zoya
AU - Wang, Derek
AU - Engrav, Tlali
AU - Wang, Reyna
AU - Gupta, Ashwin
AU - He, Weilong
AU - Moscoso-Barrera, William D.
AU - Grimes, Ayden
AU - Millán, José del R.
AU - Wang, Huiliang
TI - Highly stretchable, hair-compatible multichannel neural interface with time-stable hydrogel for high-fidelity long-term EEG sensing
T2 - Science advances
J2 - Sci Adv
PY - 2026
DA - 2026/
VL - 12
IS - 40
SP - eaee1540
SN - 2375-2548
PB - American Association for the Advancement of Science
DO - 10.1126/
UR - https://
LA - en
ER -
CSL-JSON
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