文献类型：期刊文献

英文题名：Highly sensitive, breathable, and superhydrophobic dome structure nonwoven-based flexible pressure sensor utilizing machine learning for handwriting recognition

作者：Wang, Jian[1,2,3,5];Zhang, Rui[1,2,3];Wang, Yi-Fei[4];Ying, Di[1];Zheng, Yingying[1];Wang, Chaoxia[5];Zou, Zhuanyong[1,2,3]

机构：[1]Shaoxing Univ, Shaoxing Key Lab High Performance Fibers & Prod, Shaoxing 312000, Zhejiang, Peoples R China;[2]Shaoxing Univ, Natl Engn Res Ctr Fiber based Composites, Shaoxing Subctr, Shaoxing 312000, Zhejiang, Peoples R China;[3]Key Lab Clean Dyeing & Finishing Technol Zhejiang, Shaoxing 312000, Zhejiang, Peoples R China;[4]Yamagata Univ, Res Ctr Organ Elect, 4-3-16 Jonan, Yonezawa, Yamagata 9928510, Japan;[5]Jiangnan Univ, Sch Text Sci & Engn, Wuxi 214122, Jiangsu, Peoples R China

年份：2025

卷号：300

外文期刊名：INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES

收录：SCI-EXPANDED(收录号：WOS:001413715400001)、、EI(收录号：20250417759597)、Scopus(收录号：2-s2.0-85215863458)、WOS

基金：This research was financially supported by the General Scientific Research Project of Zhejiang Education Department (Y202351466), Shaoxing Basic Public Welfare Planning Project (2024A11019) and Zhejiang Provincial Science and Technology Innovation Program (New Young Talent Program) for College Students (2023R465032).

语种：英文

外文关键词：Dome structure; Flexible pressure sensor; Health monitoring; Machine learning; Handwriting recognition

外文摘要：Wearable devices that incorporate flexible pressure sensors have shown great potential for human-machine interaction, speech recognition, health monitoring, and handwriting recognition. However, achieving high sensitivity, durability, wide detection range, and breathability through cost-effective fabrication remains challenging. Through ultrasound-assisted modification and impregnation-drying, dome-structured nonwovens/rGO/ PDMS flexible pressure sensors were developed. The sensor exhibits high sensitivity (up to 0.65 kPa(- 1) in the range of 0-1.12 kPa), rapid response/recovery times (73/98 ms), a wide detection range (0-202 kPa), and superhydrophobic properties with a water contact angle of 166 degrees. Additionally, it demonstrates excellent breathability (514.8 mm/s) and stability (>9000 cycles). With these excellent properties, the sensor is able to detect different pressure signals, allowing encrypted information to be transmitted; it can also be used for health monitoring and motion detection. Additionally, machine learning technology is also successfully used to recognize various handwritten words, with a 94 % accuracy rate in all cases. Consequently, the developed flexible pressure sensor has a wide range of potential applications, including information encryption, medical monitoring, motion detection, human-computer interaction, and handwriting recognition.