MXene-Enabled Self-Adaptive Hydrogel Interface for Active Electroencephalogram Interactions
Human–machine interaction plays a significant role in promoting convenience, production efficiency, and usage experience. Because of the universality and characteristics of electroencephalogram (EEG) signals, active EEG interaction is a promising and cutting-edge method for human–machine interaction...
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Veröffentlicht in: | ACS nano 2022-11, Vol.16 (11), p.19373-19384 |
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Hauptverfasser: | , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Human–machine interaction plays a significant role in promoting convenience, production efficiency, and usage experience. Because of the universality and characteristics of electroencephalogram (EEG) signals, active EEG interaction is a promising and cutting-edge method for human–machine interaction. The seamless, skin-compliant, and motion-robust human–machine interface (HMI) for active EEG interaction has been in focus. Herein, we report a self-adaptive HMI (PAAS-MXene hydrogel) that can activate rapid gelation (5 s) using MXene cross-linking and conformably self-adapt to the scalp to help improve signal transduction. In addition to exhibiting satisfactory skin compliance, appropriate adhesion, and good biocompatibility, PAAS-MXene has demonstrated electrical performance reliability, such as low impedance ( |
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ISSN: | 1936-0851 1936-086X |
DOI: | 10.1021/acsnano.2c08961 |