Multi-day recalibration-free electrophysiology interface based on carbon nanotube thin film dry electrodes

Electrophysiological signals provide crucial and reliable information for decoding behavioral and cognitive human states. However, existing electrode interfaces are susceptible to artifacts or drift over time, thereby requiring frequent machine-learning model retraining. Here we present an end-to-end design of dry electrodes based on carbon nanotube (CNT) thin films, synthesized by a roll-to-roll floating catalyst chemical vapor deposition process.

By balancing structural and electrical properties, we achieved low electrode-skin impedance, high signal fidelity, minimal motion artifacts, high breathability, and biocompatibility, outperforming the gold standard wet electrodes. In a multichannel myoelectric interface demonstration, these CNT electrodes maintained stable signals and consistent task performance across 14 days using only minutes of training data and no further model retraining. To our knowledge, this is the first demonstration of a multi-day recalibration-free dry electrode system under naturalistic conditions, achieved by stable electrode–skin interface, rather than ongoing algorithmic adaptation.

Paddy Chan for valuable discussions. This work was supported by the National Institutes of Health under grant nos. U01EB029427 and R01MH127104, and by the Honda Research Institute.

Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, CA, USA Yuhan Wen, Hanna Hedwig Schlegel, Preeya Khanna & Ana Claudia Arias Honda Research Institute USA, Inc., San Jose, CA, USA Yuhan Wen, David Fox, Avetik Harutyunyan & Qiang Zhang Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, CA, USA Department of Naval Architecture and Ocean Engineering, Shanghai Jiao Tong University, Shanghai, China Department of Neuroscience, University of California Berkeley, Berkeley, CA, USA Correspondence to Qiang Zhang, Preeya Khanna or Ana Claudia Arias. The authors declare no competing interests. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Wen, Y., Schlegel, H.H., Fox, D. et al. Multi-day recalibration-free electrophysiology interface based on carbon nanotube thin film dry electrodes.