{"title":"Wearable Single-Electrode Capacitive Sensor with Large Penetration Depth for Intelligent Deep Tissue and Hemorrhage Monitoring","authors":"Yu-Jen Cheng, Shawn Kim, Nathan White, Xu Wang, Kristyn Ringgold, Lauren Neidig, Younghoon Kwon, Jae-Hyun Chung","doi":"10.1002/adsr.202400143","DOIUrl":null,"url":null,"abstract":"<p>Monitoring deep tissue biometrics is crucial in various clinical settings, including internal hemorrhage. Although optical and impedance tomography techniques offer real-time monitoring with minimal medical infrastructure, they still face challenges in accurately assessing deeper tissues in wearable formats. This study introduces a novel single-electrode capacitive sensor designed to measure deep tissue capacitance changes caused by variations in dielectric constant and pressure. The sensor features a carbon nanotube-paper composite (CPC) electrode integrated with a multi-walled carbon nanotube (MWCNT)-embedded foam. The CPC electrode, with its large surface area and high-aspect-ratio fibers, generates a high electric field for deeper tissue penetration, improving deep tissue monitoring performance. Penetration depth is characterized using surrogate tissue, heart, and lung models. Additionally, the integration of pressure-sensitive MWCNT foam significantly enhances the sensitivity, enabling precise detection of regional blood volume and tissue displacement. The novel sensing mechanism is applied to detect internal hemorrhage in a porcine model. By employing a machine learning algorithm, the sensor accurately estimates the severity of internal hemorrhage, offering a noninvasive alternative to catheter-based systems. This advancement lays the foundation for a real-time wearable system that monitors deep tissue health metrics, such as blood volume, blood pressure, as well as heart and lung functions.</p>","PeriodicalId":100037,"journal":{"name":"Advanced Sensor Research","volume":"4 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adsr.202400143","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Sensor Research","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/adsr.202400143","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Monitoring deep tissue biometrics is crucial in various clinical settings, including internal hemorrhage. Although optical and impedance tomography techniques offer real-time monitoring with minimal medical infrastructure, they still face challenges in accurately assessing deeper tissues in wearable formats. This study introduces a novel single-electrode capacitive sensor designed to measure deep tissue capacitance changes caused by variations in dielectric constant and pressure. The sensor features a carbon nanotube-paper composite (CPC) electrode integrated with a multi-walled carbon nanotube (MWCNT)-embedded foam. The CPC electrode, with its large surface area and high-aspect-ratio fibers, generates a high electric field for deeper tissue penetration, improving deep tissue monitoring performance. Penetration depth is characterized using surrogate tissue, heart, and lung models. Additionally, the integration of pressure-sensitive MWCNT foam significantly enhances the sensitivity, enabling precise detection of regional blood volume and tissue displacement. The novel sensing mechanism is applied to detect internal hemorrhage in a porcine model. By employing a machine learning algorithm, the sensor accurately estimates the severity of internal hemorrhage, offering a noninvasive alternative to catheter-based systems. This advancement lays the foundation for a real-time wearable system that monitors deep tissue health metrics, such as blood volume, blood pressure, as well as heart and lung functions.