Robust, self-adhesive, and low-contact impedance polyvinyl alcohol/polyacrylamide dual-network hydrogel semidry electrode for biopotential signal acquisition
Guangli Li , Ying Liu , Yuwei Chen , Yonghui Xia , Xiaoman Qi , Xuan Wan , Yuan Jin , Jun Liu , Quanguo He , Kanghua Li , Jianxin Tang
SmartMat ›› 2024, Vol. 5 ›› Issue (2) : e1173
Robust, self-adhesive, and low-contact impedance polyvinyl alcohol/polyacrylamide dual-network hydrogel semidry electrode for biopotential signal acquisition
Herein, we fabricated a flexible semidry electrode with excellent mechanical performance, satisfactory self-adhesiveness, and low-contact impedance using physical/chemical crosslinked polyvinyl alcohol/polyacrylamide dual-network hydrogels (PVA/PAM DNHs) as an efficient saline reservoir. The resultant PVA/PAM DNHs showed admirable adhesive and compliance to the hairy scalp, facilitating the establishment of a robust electrode/skin interface for biopotential signal transmission. Moreover, the PVA/PAM DNHs steadily released trace saline onto the scalp to achieve the minimized potential drift (1.47 ± 0.39 mV/min) and low electrode–scalp impedance (18.2 ± 8.9 kΩ @ 10 Hz). More importantly, the application feasibility of real-world brain−computer interfaces (BCIs) was preliminarily validated by 10 participants using two classic BCI paradigms. The mean temporal cross-correlation coefficients between the semidry and wet electrodes in the eyes open/closed and the N200 speller paradigms are 0.919 ± 0.054 and 0.912 ± 0.050, respectively. Both electrodes demonstrate anticipated neuroelectrophysiological responses with similar patterns. This semidry electrode could also effectively capture robust P-QRS-T peaks during electrocardiogram recording. Considering their outstanding advantages of fast setup, user-friendliness, and robust signals, the proposed PVA/PAM DNH-based electrode is a promising alternative to wet electrodes in biopotential signal acquisition.
brain–computer interface / dual-network hydrogel / electrocardiogram signals / electroencephalography signals / semidry electrode
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2023 The Authors. SmartMat published by Tianjin University and John Wiley & Sons Australia, Ltd.
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