Tianrui Cui, Ying-Fen Zeng, Xiaoshi Li, Y. Qiao, Ding Li, H. Tian, Yi Yang, Si-Fan Yang, Tian-ling Ren
{"title":"用于长期脑电图监测的透气柔性电子皮肤","authors":"Tianrui Cui, Ying-Fen Zeng, Xiaoshi Li, Y. Qiao, Ding Li, H. Tian, Yi Yang, Si-Fan Yang, Tian-ling Ren","doi":"10.1109/EDTM55494.2023.10103024","DOIUrl":null,"url":null,"abstract":"Daily long-term, real-time monitoring of electroencephalogram (EEG) signals is essential for disease diagnosis, health monitoring, and brain-computer interaction. This work presents a breathable and flexible graphene-polyurethane (PU) mesh electronic skin (GPMES). With excellent breathability (1.904 $\\text{kg}\\cdot \\mathrm{m}^{-2}\\cdot \\text{day}^{-1}$ at body temperature) comparable to naked skin, good flexibility, lightweight (1.5 mg), and low electrode-skin impedance (4.683 $\\mathrm{k}\\Omega$ at 1 kHz), the GPMES can be a promising candidate interface for long-term (> 10 h) and reliable daily EEG monitoring.","PeriodicalId":418413,"journal":{"name":"2023 7th IEEE Electron Devices Technology & Manufacturing Conference (EDTM)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Breathable and Flexible Electronic Skin for Long-Term Electroencephalogram Monitoring\",\"authors\":\"Tianrui Cui, Ying-Fen Zeng, Xiaoshi Li, Y. Qiao, Ding Li, H. Tian, Yi Yang, Si-Fan Yang, Tian-ling Ren\",\"doi\":\"10.1109/EDTM55494.2023.10103024\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Daily long-term, real-time monitoring of electroencephalogram (EEG) signals is essential for disease diagnosis, health monitoring, and brain-computer interaction. This work presents a breathable and flexible graphene-polyurethane (PU) mesh electronic skin (GPMES). With excellent breathability (1.904 $\\\\text{kg}\\\\cdot \\\\mathrm{m}^{-2}\\\\cdot \\\\text{day}^{-1}$ at body temperature) comparable to naked skin, good flexibility, lightweight (1.5 mg), and low electrode-skin impedance (4.683 $\\\\mathrm{k}\\\\Omega$ at 1 kHz), the GPMES can be a promising candidate interface for long-term (> 10 h) and reliable daily EEG monitoring.\",\"PeriodicalId\":418413,\"journal\":{\"name\":\"2023 7th IEEE Electron Devices Technology & Manufacturing Conference (EDTM)\",\"volume\":\"83 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 7th IEEE Electron Devices Technology & Manufacturing Conference (EDTM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EDTM55494.2023.10103024\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 7th IEEE Electron Devices Technology & Manufacturing Conference (EDTM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EDTM55494.2023.10103024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Breathable and Flexible Electronic Skin for Long-Term Electroencephalogram Monitoring
Daily long-term, real-time monitoring of electroencephalogram (EEG) signals is essential for disease diagnosis, health monitoring, and brain-computer interaction. This work presents a breathable and flexible graphene-polyurethane (PU) mesh electronic skin (GPMES). With excellent breathability (1.904 $\text{kg}\cdot \mathrm{m}^{-2}\cdot \text{day}^{-1}$ at body temperature) comparable to naked skin, good flexibility, lightweight (1.5 mg), and low electrode-skin impedance (4.683 $\mathrm{k}\Omega$ at 1 kHz), the GPMES can be a promising candidate interface for long-term (> 10 h) and reliable daily EEG monitoring.