Taewi Kim, Insic Hong, Yeonwook Roh, Dongjin Kim, Sungwook Kim, Sunghoon Im, Changhwan Kim, Kiwon Jang, Seongyeon Kim, Minho Kim, Jieun Park, Dohyeon Gong, Kihyeon Ahn, Jingoo Lee, Gunhee Lee, Hak-Seung Lee, Jeehoon Kang, Ji Man Hong, Seungchul Lee, Sungchul Seo, Bon-Kwon Koo, Je-sung Koh, Seungyong Han, Daeshik Kang
{"title":"生物医学应用的蜘蛛式可调机械传感器","authors":"Taewi Kim, Insic Hong, Yeonwook Roh, Dongjin Kim, Sungwook Kim, Sunghoon Im, Changhwan Kim, Kiwon Jang, Seongyeon Kim, Minho Kim, Jieun Park, Dohyeon Gong, Kihyeon Ahn, Jingoo Lee, Gunhee Lee, Hak-Seung Lee, Jeehoon Kang, Ji Man Hong, Seungchul Lee, Sungchul Seo, Bon-Kwon Koo, Je-sung Koh, Seungyong Han, Daeshik Kang","doi":"10.1038/s41528-023-00247-2","DOIUrl":null,"url":null,"abstract":"The recent advances of wearable sensors are remarkable but there are still limitations that they need to be refabricated to tune the sensor for target signal. However, biological sensory systems have the inherent potential to adjust their sensitivity according to the external environment, allowing for a broad and enhanced detection. Here, we developed a Tunable, Ultrasensitive, Nature-inspired, Epidermal Sensor (TUNES) that the strain sensitivity was dramatically increased (GF ~30k) and the pressure sensitivity could be tuned (10–254 kPa−1) by preset membrane tension. The sensor adjusts the sensitivity to the pressure regime by preset tension, so it can measure a wide range (0.05 Pa–25 kPa) with the best performance: from very small signals such as minute pulse to relatively large signals such as muscle contraction and respiration. We verified its capabilities as a wearable health monitoring system by clinical trial comparing with pressure wire which is considered the current gold standard of blood pressure (r = 0.96) and home health care system by binary classification of Old’s/Young’s pulse waves via machine learning (accuracy 95%).","PeriodicalId":48528,"journal":{"name":"npj Flexible Electronics","volume":null,"pages":null},"PeriodicalIF":12.3000,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41528-023-00247-2.pdf","citationCount":"4","resultStr":"{\"title\":\"Spider-inspired tunable mechanosensor for biomedical applications\",\"authors\":\"Taewi Kim, Insic Hong, Yeonwook Roh, Dongjin Kim, Sungwook Kim, Sunghoon Im, Changhwan Kim, Kiwon Jang, Seongyeon Kim, Minho Kim, Jieun Park, Dohyeon Gong, Kihyeon Ahn, Jingoo Lee, Gunhee Lee, Hak-Seung Lee, Jeehoon Kang, Ji Man Hong, Seungchul Lee, Sungchul Seo, Bon-Kwon Koo, Je-sung Koh, Seungyong Han, Daeshik Kang\",\"doi\":\"10.1038/s41528-023-00247-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The recent advances of wearable sensors are remarkable but there are still limitations that they need to be refabricated to tune the sensor for target signal. However, biological sensory systems have the inherent potential to adjust their sensitivity according to the external environment, allowing for a broad and enhanced detection. Here, we developed a Tunable, Ultrasensitive, Nature-inspired, Epidermal Sensor (TUNES) that the strain sensitivity was dramatically increased (GF ~30k) and the pressure sensitivity could be tuned (10–254 kPa−1) by preset membrane tension. The sensor adjusts the sensitivity to the pressure regime by preset tension, so it can measure a wide range (0.05 Pa–25 kPa) with the best performance: from very small signals such as minute pulse to relatively large signals such as muscle contraction and respiration. We verified its capabilities as a wearable health monitoring system by clinical trial comparing with pressure wire which is considered the current gold standard of blood pressure (r = 0.96) and home health care system by binary classification of Old’s/Young’s pulse waves via machine learning (accuracy 95%).\",\"PeriodicalId\":48528,\"journal\":{\"name\":\"npj Flexible Electronics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":12.3000,\"publicationDate\":\"2023-03-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.nature.com/articles/s41528-023-00247-2.pdf\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"npj Flexible Electronics\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://www.nature.com/articles/s41528-023-00247-2\",\"RegionNum\":1,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"npj Flexible Electronics","FirstCategoryId":"88","ListUrlMain":"https://www.nature.com/articles/s41528-023-00247-2","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Spider-inspired tunable mechanosensor for biomedical applications
The recent advances of wearable sensors are remarkable but there are still limitations that they need to be refabricated to tune the sensor for target signal. However, biological sensory systems have the inherent potential to adjust their sensitivity according to the external environment, allowing for a broad and enhanced detection. Here, we developed a Tunable, Ultrasensitive, Nature-inspired, Epidermal Sensor (TUNES) that the strain sensitivity was dramatically increased (GF ~30k) and the pressure sensitivity could be tuned (10–254 kPa−1) by preset membrane tension. The sensor adjusts the sensitivity to the pressure regime by preset tension, so it can measure a wide range (0.05 Pa–25 kPa) with the best performance: from very small signals such as minute pulse to relatively large signals such as muscle contraction and respiration. We verified its capabilities as a wearable health monitoring system by clinical trial comparing with pressure wire which is considered the current gold standard of blood pressure (r = 0.96) and home health care system by binary classification of Old’s/Young’s pulse waves via machine learning (accuracy 95%).
期刊介绍:
npj Flexible Electronics is an online-only and open access journal, which publishes high-quality papers related to flexible electronic systems, including plastic electronics and emerging materials, new device design and fabrication technologies, and applications.