Zhang, M., Hao, M., Liu, B., Chen, J., Ren, G., Zhao, Y., Guo, J., Zhuang, L., Zhao, S., Peng, Z., Lian, J., Wu, J., Chen, Y., Ma, J., & Lu, Q. (2024). Recent progress of hydrogels in brain-machine interface. Soft Science, 4(4), Article 39. https://doi.org/10.20517/ss.2024.34
Zhang, Mingxuan ; Hao, Mingming ; Liu, Botao et al. / Recent progress of hydrogels in brain-machine interface. In: Soft Science. 2024 ; Vol. 4, No. 4.
@article{97fdb9b35ecd47f7aa2923380e5a731f,
title = "Recent progress of hydrogels in brain-machine interface",
abstract = "The long-term stable monitoring of brain signals, including electroencephalogram (EEG), electrocorticogram (ECoG) and local field potential (LFP), is of great significance for the fundamental research in brain science, artificial intelligence and the diagnosis and treatment of brain-related disorders. Therefore, both non-invasive and invasive brain-machine interfaces based on different materials and structures have been widely studied due to their unique performance. Among these materials, hydrogels have emerged as a promising interface material for brain signal collection systems due to their similar mechanical properties to biological tissues, excellent biocompatibility, strong self-adhesive properties, and exceptional ionic conductive characteristics. This review aims to provide an overview on the recent progress of hydrogel-based brain interfaces in the recording of brain signals with noninvasive and invasive methods. It is expected that this paper will serve as a valuable summary and reference for future research in the hydrogel-based brain interface.",
keywords = "brain science, Brain-machine interface, flexible electronics, hydrogels, neural signal",
author = "Mingxuan Zhang and Mingming Hao and Botao Liu and Jianping Chen and Guoqiang Ren and Yinchao Zhao and Jinxiu Guo and Liping Zhuang and Shunying Zhao and Zhaoxiang Peng and Jiangfang Lian and Jingjin Wu and Yi Chen and Jingyun Ma and Qifeng Lu",
year = "2024",
month = nov,
day = "27",
doi = "10.20517/ss.2024.34",
language = "English",
volume = "4",
journal = "Soft Science",
issn = "2769-5441",
number = "4",
}
Zhang, M, Hao, M, Liu, B, Chen, J, Ren, G, Zhao, Y, Guo, J, Zhuang, L, Zhao, S, Peng, Z, Lian, J, Wu, J, Chen, Y, Ma, J & Lu, Q 2024, 'Recent progress of hydrogels in brain-machine interface', Soft Science, vol. 4, no. 4, 39. https://doi.org/10.20517/ss.2024.34
Recent progress of hydrogels in brain-machine interface. / Zhang, Mingxuan; Hao, Mingming; Liu, Botao et al.
In:
Soft Science, Vol. 4, No. 4, 39, 27.11.2024.
Research output: Contribution to journal › Review article › peer-review
TY - JOUR
T1 - Recent progress of hydrogels in brain-machine interface
AU - Zhang, Mingxuan
AU - Hao, Mingming
AU - Liu, Botao
AU - Chen, Jianping
AU - Ren, Guoqiang
AU - Zhao, Yinchao
AU - Guo, Jinxiu
AU - Zhuang, Liping
AU - Zhao, Shunying
AU - Peng, Zhaoxiang
AU - Lian, Jiangfang
AU - Wu, Jingjin
AU - Chen, Yi
AU - Ma, Jingyun
AU - Lu, Qifeng
PY - 2024/11/27
Y1 - 2024/11/27
N2 - The long-term stable monitoring of brain signals, including electroencephalogram (EEG), electrocorticogram (ECoG) and local field potential (LFP), is of great significance for the fundamental research in brain science, artificial intelligence and the diagnosis and treatment of brain-related disorders. Therefore, both non-invasive and invasive brain-machine interfaces based on different materials and structures have been widely studied due to their unique performance. Among these materials, hydrogels have emerged as a promising interface material for brain signal collection systems due to their similar mechanical properties to biological tissues, excellent biocompatibility, strong self-adhesive properties, and exceptional ionic conductive characteristics. This review aims to provide an overview on the recent progress of hydrogel-based brain interfaces in the recording of brain signals with noninvasive and invasive methods. It is expected that this paper will serve as a valuable summary and reference for future research in the hydrogel-based brain interface.
AB - The long-term stable monitoring of brain signals, including electroencephalogram (EEG), electrocorticogram (ECoG) and local field potential (LFP), is of great significance for the fundamental research in brain science, artificial intelligence and the diagnosis and treatment of brain-related disorders. Therefore, both non-invasive and invasive brain-machine interfaces based on different materials and structures have been widely studied due to their unique performance. Among these materials, hydrogels have emerged as a promising interface material for brain signal collection systems due to their similar mechanical properties to biological tissues, excellent biocompatibility, strong self-adhesive properties, and exceptional ionic conductive characteristics. This review aims to provide an overview on the recent progress of hydrogel-based brain interfaces in the recording of brain signals with noninvasive and invasive methods. It is expected that this paper will serve as a valuable summary and reference for future research in the hydrogel-based brain interface.
KW - brain science
KW - Brain-machine interface
KW - flexible electronics
KW - hydrogels
KW - neural signal
U2 - 10.20517/ss.2024.34
DO - 10.20517/ss.2024.34
M3 - Review article
SN - 2769-5441
VL - 4
JO - Soft Science
JF - Soft Science
IS - 4
M1 - 39
ER -
Zhang M, Hao M, Liu B, Chen J, Ren G, Zhao Y et al. Recent progress of hydrogels in brain-machine interface. Soft Science. 2024 Nov 27;4(4):39. doi: 10.20517/ss.2024.34
