A selective frequency damping and Janus adhesive hydrogel as bioelectronic interfaces for clinical trials

Jiabei Luo, Yuefan Jin, Linpeng Li (), Boya Chang, Bin Zhang, Kerui Li, Yaogang Li, Qinghong Zhang, Hongzhi Wang, Jing Wang, Shankai Yin, Hui Wang () and Chengyi Hou ()
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Jiabei Luo: Donghua University
Yuefan Jin: Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine
Linpeng Li: Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine
Boya Chang: Donghua University
Bin Zhang: Donghua University
Kerui Li: Donghua University
Yaogang Li: Donghua University
Qinghong Zhang: Donghua University
Hongzhi Wang: Donghua University
Jing Wang: ETH Zürich
Shankai Yin: Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine
Hui Wang: Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine
Chengyi Hou: Donghua University

Nature Communications, 2024, vol. 15, issue 1, 1-10

Abstract: Abstract Maintaining stillness is essential for accurate bioelectrical signal acquisition, but dynamic noise from breathing remains unavoidable. Isotropic adhesives are often used as bioelectronic interfaces to ensure signal fidelity, but they can leave irreversible residues, compromising device accuracy. We propose a hydrogel with selective frequency damping and asymmetric adhesion as a bioelectronic interface. This hydrogel mitigates dynamic noise from breathing, with a damping effect in the breathing frequency range 60 times greater than at other frequencies. It also exhibits an asymmetric adhesion difference of up to 537 times, preventing residues. By homogenizing ion distribution, extending Debye length, and densifying the electric field, the hydrogel ensures stable signal transmission over 10,000 cycles. Additionally, it can non-invasively diagnose otitis media with higher sensitivity than invasive probes and has been effective in clinical polysomnography monitoring, aiding in the diagnosis of obstructive sleep apnea.

Date: 2024
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DOI: 10.1038/s41467-024-52833-1

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