基于三聚氰胺框架石墨烯气凝胶的中医脉搏记录与识别压力传感器

IF 4.3 2区 综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Bo Li;Keshuai Yang;Yizhao Zhou;Chengbing Fang;Chengqi Zhang;Xian Song;Yaoran Sun;Pengyu Wang;Tong Li;Yuxin Peng;Fang Han
{"title":"基于三聚氰胺框架石墨烯气凝胶的中医脉搏记录与识别压力传感器","authors":"Bo Li;Keshuai Yang;Yizhao Zhou;Chengbing Fang;Chengqi Zhang;Xian Song;Yaoran Sun;Pengyu Wang;Tong Li;Yuxin Peng;Fang Han","doi":"10.1109/JSEN.2025.3561953","DOIUrl":null,"url":null,"abstract":"In this article, we developed a graphene-melamine graphene aerogel sensor to integrate the traditional Chinese medicine (TCM) pulse diagnosis with modern information technologies. Owing to the reduced graphene oxide (GO) network embedded in the melamine frame, the sensor demonstrates a high gauge factor (GF) of 596.2 with high repeatability, enhancing the accuracy of pulse signal detection. Moreover, the porous structure of the sensing material augments its piezoresistive properties, exhibiting a “fast-then-slow” pattern in resistance changes. The reasonable pulse signal is collected by experienced TCM practitioners accurately locating specific pulse points—Cun, Guan, and Chi—and applying the optimal pressure with the proposed sensor adhered on their fingertip. By employing continuous wavelet transform (CWT) and ResNet-50 for advanced signal processing and classification, the study attains a classification accuracy of 90.1% in differentiating pulse patterns between pregnant and nonpregnant women. This high level of accuracy demonstrates the potential of integrating this technology to standardize and validate TCM diagnostic techniques, potentially broadening the acceptance of TCM in global health systems.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 12","pages":"21185-21193"},"PeriodicalIF":4.3000,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pressure Sensor Based on Melamine Frame Graphene Aerogel for Pulse Recording and Identification in Traditional Chinese Medicine\",\"authors\":\"Bo Li;Keshuai Yang;Yizhao Zhou;Chengbing Fang;Chengqi Zhang;Xian Song;Yaoran Sun;Pengyu Wang;Tong Li;Yuxin Peng;Fang Han\",\"doi\":\"10.1109/JSEN.2025.3561953\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this article, we developed a graphene-melamine graphene aerogel sensor to integrate the traditional Chinese medicine (TCM) pulse diagnosis with modern information technologies. Owing to the reduced graphene oxide (GO) network embedded in the melamine frame, the sensor demonstrates a high gauge factor (GF) of 596.2 with high repeatability, enhancing the accuracy of pulse signal detection. Moreover, the porous structure of the sensing material augments its piezoresistive properties, exhibiting a “fast-then-slow” pattern in resistance changes. The reasonable pulse signal is collected by experienced TCM practitioners accurately locating specific pulse points—Cun, Guan, and Chi—and applying the optimal pressure with the proposed sensor adhered on their fingertip. By employing continuous wavelet transform (CWT) and ResNet-50 for advanced signal processing and classification, the study attains a classification accuracy of 90.1% in differentiating pulse patterns between pregnant and nonpregnant women. This high level of accuracy demonstrates the potential of integrating this technology to standardize and validate TCM diagnostic techniques, potentially broadening the acceptance of TCM in global health systems.\",\"PeriodicalId\":447,\"journal\":{\"name\":\"IEEE Sensors Journal\",\"volume\":\"25 12\",\"pages\":\"21185-21193\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2025-04-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Sensors Journal\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10980200/\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Journal","FirstCategoryId":"103","ListUrlMain":"https://ieeexplore.ieee.org/document/10980200/","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

摘要

在本文中,我们开发了一种石墨烯-三聚氰胺石墨烯气凝胶传感器,将中医脉搏诊断与现代信息技术相结合。由于在三聚氰胺框架中嵌入了还原氧化石墨烯(GO)网络,该传感器具有596.2的高测量因子(GF),具有高重复性,提高了脉冲信号检测的准确性。此外,传感材料的多孔结构增强了其压阻特性,在电阻变化中表现出“先快后慢”的模式。由经验丰富的中医医生采集合理的脉搏信号,准确定位特定的脉搏点——村、关、气,并将所提出的传感器贴在指尖上施加最佳压力。采用连续小波变换(CWT)和ResNet-50进行高级信号处理和分类,对孕妇和非孕妇脉搏模式的分类准确率达到90.1%。这种高水平的准确性显示了整合该技术标准化和验证中医诊断技术的潜力,有可能扩大中医在全球卫生系统中的接受程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pressure Sensor Based on Melamine Frame Graphene Aerogel for Pulse Recording and Identification in Traditional Chinese Medicine
In this article, we developed a graphene-melamine graphene aerogel sensor to integrate the traditional Chinese medicine (TCM) pulse diagnosis with modern information technologies. Owing to the reduced graphene oxide (GO) network embedded in the melamine frame, the sensor demonstrates a high gauge factor (GF) of 596.2 with high repeatability, enhancing the accuracy of pulse signal detection. Moreover, the porous structure of the sensing material augments its piezoresistive properties, exhibiting a “fast-then-slow” pattern in resistance changes. The reasonable pulse signal is collected by experienced TCM practitioners accurately locating specific pulse points—Cun, Guan, and Chi—and applying the optimal pressure with the proposed sensor adhered on their fingertip. By employing continuous wavelet transform (CWT) and ResNet-50 for advanced signal processing and classification, the study attains a classification accuracy of 90.1% in differentiating pulse patterns between pregnant and nonpregnant women. This high level of accuracy demonstrates the potential of integrating this technology to standardize and validate TCM diagnostic techniques, potentially broadening the acceptance of TCM in global health systems.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
IEEE Sensors Journal
IEEE Sensors Journal 工程技术-工程:电子与电气
CiteScore
7.70
自引率
14.00%
发文量
2058
审稿时长
5.2 months
期刊介绍: The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信