{"title":"类安全气囊梳状柔性压力传感器及其可穿戴应用","authors":"Yingxi Xie, Sheng Bian, Longsheng Lu, Hanxian Chen, Jiayue Liao, Yuxuan Liang, Xiaohua Wu","doi":"10.1021/acsami.5c05118","DOIUrl":null,"url":null,"abstract":"Flexible wearable devices demonstrate immense potential in healthcare and human–computer interaction, yet the development of high-performance flexible pressure sensors for these applications remains a pressing technical challenge. Inspired by the structure of commonly used airbag combs, an airbag-like comb flexible pressure sensor (ALCS) was designed and fabricated using laser direct writing (LDW) technology. By incorporating an airbag structure to enhance the variation in contact area between the sensing and electrode layers, coupled with pore design to further boost unit strain, the ALCS achieved an ultrawide detection range (1.27–2783.815 kPa), high sensitivity (up to 21.53 kPa<sup>–1</sup>), and exceptionally fast response/recovery times (3.4 ms/34 ms). To tackle the issue of lacking dynamic sign language recognition systems, we fabricated an intelligent glove (ALCIG) based on ALCS, which, when integrated with machine learning algorithms, achieved precise recognition of 8 types of dynamic sign language, offering an efficient solution for barrier-free communication for individuals with speech impairments. To further evaluate the recognition capabilities of ALCIG and enhance its applicability in diverse scenarios, we developed a virtual keyboard letter recognition test involving 26 categories. The results demonstrated that even with 26 highly complex targets, ALCIG successfully collected data and achieved accurate classification, showcasing its significant potential in gesture recognition and complex classification tasks.","PeriodicalId":5,"journal":{"name":"ACS Applied Materials & Interfaces","volume":"7 1","pages":""},"PeriodicalIF":8.2000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Airbag-like Comb Flexible Pressure Sensor and Its Wearable Applications\",\"authors\":\"Yingxi Xie, Sheng Bian, Longsheng Lu, Hanxian Chen, Jiayue Liao, Yuxuan Liang, Xiaohua Wu\",\"doi\":\"10.1021/acsami.5c05118\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Flexible wearable devices demonstrate immense potential in healthcare and human–computer interaction, yet the development of high-performance flexible pressure sensors for these applications remains a pressing technical challenge. Inspired by the structure of commonly used airbag combs, an airbag-like comb flexible pressure sensor (ALCS) was designed and fabricated using laser direct writing (LDW) technology. By incorporating an airbag structure to enhance the variation in contact area between the sensing and electrode layers, coupled with pore design to further boost unit strain, the ALCS achieved an ultrawide detection range (1.27–2783.815 kPa), high sensitivity (up to 21.53 kPa<sup>–1</sup>), and exceptionally fast response/recovery times (3.4 ms/34 ms). To tackle the issue of lacking dynamic sign language recognition systems, we fabricated an intelligent glove (ALCIG) based on ALCS, which, when integrated with machine learning algorithms, achieved precise recognition of 8 types of dynamic sign language, offering an efficient solution for barrier-free communication for individuals with speech impairments. To further evaluate the recognition capabilities of ALCIG and enhance its applicability in diverse scenarios, we developed a virtual keyboard letter recognition test involving 26 categories. The results demonstrated that even with 26 highly complex targets, ALCIG successfully collected data and achieved accurate classification, showcasing its significant potential in gesture recognition and complex classification tasks.\",\"PeriodicalId\":5,\"journal\":{\"name\":\"ACS Applied Materials & Interfaces\",\"volume\":\"7 1\",\"pages\":\"\"},\"PeriodicalIF\":8.2000,\"publicationDate\":\"2025-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Materials & Interfaces\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1021/acsami.5c05118\",\"RegionNum\":2,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Materials & Interfaces","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1021/acsami.5c05118","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
Airbag-like Comb Flexible Pressure Sensor and Its Wearable Applications
Flexible wearable devices demonstrate immense potential in healthcare and human–computer interaction, yet the development of high-performance flexible pressure sensors for these applications remains a pressing technical challenge. Inspired by the structure of commonly used airbag combs, an airbag-like comb flexible pressure sensor (ALCS) was designed and fabricated using laser direct writing (LDW) technology. By incorporating an airbag structure to enhance the variation in contact area between the sensing and electrode layers, coupled with pore design to further boost unit strain, the ALCS achieved an ultrawide detection range (1.27–2783.815 kPa), high sensitivity (up to 21.53 kPa–1), and exceptionally fast response/recovery times (3.4 ms/34 ms). To tackle the issue of lacking dynamic sign language recognition systems, we fabricated an intelligent glove (ALCIG) based on ALCS, which, when integrated with machine learning algorithms, achieved precise recognition of 8 types of dynamic sign language, offering an efficient solution for barrier-free communication for individuals with speech impairments. To further evaluate the recognition capabilities of ALCIG and enhance its applicability in diverse scenarios, we developed a virtual keyboard letter recognition test involving 26 categories. The results demonstrated that even with 26 highly complex targets, ALCIG successfully collected data and achieved accurate classification, showcasing its significant potential in gesture recognition and complex classification tasks.
期刊介绍:
ACS Applied Materials & Interfaces is a leading interdisciplinary journal that brings together chemists, engineers, physicists, and biologists to explore the development and utilization of newly-discovered materials and interfacial processes for specific applications. Our journal has experienced remarkable growth since its establishment in 2009, both in terms of the number of articles published and the impact of the research showcased. We are proud to foster a truly global community, with the majority of published articles originating from outside the United States, reflecting the rapid growth of applied research worldwide.