Recent progress of hydrogels in brain-machine interface

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 non-invasive 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.

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Publication Details

Journal
Soft Science
Published
2024-11-27
DOI
https://doi.org/10.20517/ss.2024.34
Citations
8
Primary Topic
Neuroscience and Neural Engineering
Type
article
Field-Weighted Citation Impact
2.15
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article

Recent progress of hydrogels in brain-machine interface

Shunying Zhao, Jiangfang Lian, Yinchao Zhao, Jinxiu Guo et al.
8 citations
Soft Science
Neuroscience and Neural Engineering
2.15
article

Recent progress of hydrogels in brain-machine interface

Shunying Zhao, Jiangfang Lian, Yinchao Zhao, Jinxiu Guo, Guoqiang Ren, Jingjin Wu, Liping Zhuang, Mingxuan Zhang, Mingming Hao, Jianping Chen, Jingyun Ma, Yi Chen, Qifeng Lu, Botao Liu, Zhaoxiang Peng
article en
8 citations

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 non-invasive 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.

Soft ScienceVol. 4(4)
Ningbo University (CN)
Openalex Percentile: Top 12%
Neuroscience and Neural Engineering
2.15
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