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On-skin paintable biogel for long-term high-fidelity electroencephalogram recording

Long-term high-fidelity electroencephalogram (EEG) recordings are critical for clinical and brain science applications. Conductive liquid-like or solid-like wet interface materials have been conventionally used as reliable interfaces for EEG recording. However, because of their simplex liquid or sol...

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Detalles Bibliográficos
Autores principales: Wang, Chunya, Wang, Haoyang, Wang, Binghao, Miyata, Hiroo, Wang, Yan, Nayeem, Md Osman Goni, Kim, Jae Joon, Lee, Sunghoon, Yokota, Tomoyuki, Onodera, Hiroshi, Someya, Takao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9122322/
https://www.ncbi.nlm.nih.gov/pubmed/35594357
http://dx.doi.org/10.1126/sciadv.abo1396
Descripción
Sumario:Long-term high-fidelity electroencephalogram (EEG) recordings are critical for clinical and brain science applications. Conductive liquid-like or solid-like wet interface materials have been conventionally used as reliable interfaces for EEG recording. However, because of their simplex liquid or solid phase, electrodes with them as interfaces confront inadequate dynamic adaptability to hairy scalp, which makes it challenging to maintain stable and efficient contact of electrodes with scalp for long-term EEG recording. Here, we develop an on-skin paintable conductive biogel that shows temperature-controlled reversible fluid-gel transition to address the abovementioned limitation. This phase transition endows the biogel with unique on-skin paintability and in situ gelatinization, establishing conformal contact and dynamic compliance of electrodes with hairy scalp. The biogel is demonstrated as an efficient interface for long-term high-quality EEG recording over several days and for the high-performance capture and classification of evoked potentials. The paintable biogel offers a biocompatible and long-term reliable interface for EEG-based systems.