基于MXene/PEDOT:PSS柔性压力传感器的制备及其在唇语识别中的应用  

Preparation of flexible pressure sensor based on MXene/PEDOT:PSS and its application in lip language recognition

作　　者：钟山 贾磊 李晓春 张校亮 孟雪娟 ZHONG Shan;JIA Lei;LI Xiaochun;ZHANG Xiaoliang;MENG Xuejuan(Institute of Biomedical Precision Testing and Instrumentation,College of Biomedical Engineering,Taiyuan University of Technology,Jinzhong 030600,China)

机构地区：[1]太原理工大学生物医学工程学院,生物医学精准检测与仪器研究所,晋中030600

出　　处：《复合材料学报》2025年第1期374-385,共12页Acta Materiae Compositae Sinica

基　　金：山西省应用基础研究青年基金(202203021212265);山西省医学重点科研项目(2022XM17)。

摘　　要：唇语是声带损伤、喉舌损伤及听障患者的一种有效的语言沟通方式。唇语信号由嘴唇和面部肌肉运动而产生,其包含了大量的语音信息。通过柔性压力传感器来捕获肌肉运动可实现唇语信号的提取和识别,为听、说功能障碍患者提供了更加自然、便捷的无障碍交流方式。本研究采用二维材料MXene和高导电聚合物聚(3,4-乙基二氧噻吩):聚(苯乙烯磺酸盐)(PEDOT:PSS)作为复合材料,以可拉伸的且具有微结构的Ecoflex作为柔性基底,制备了一种压阻式柔性压力传感器。该传感器在0~2.5 kPa压力范围内具有42.31 kPa-1的高灵敏度及快速响应(<150 ms),并且在10000次压缩-释放循环测试中显示出高稳定性。将该柔性压力传感器贴附于嘴角上并捕获唇语的肌肉运动,结合卷积神经网络算法对十二生肖英语单词信号进行训练和测试,平均准确率高达90.18%。该工作增加了唇语识别系统的多样性,为唇语运动信号直接转化为语音或文本奠定了重要基础。Lip language is an effective form of verbal communication for patients with vocal cord injuries,laryngeal and tongue injuries,and hearing loss.Lip-speaking signals are generated by lip and facial muscle movements,which contain a large amount of speech information.The extraction and recognition of lip-speaking signals can be achieved by capturing the muscle movements through flexible pressure sensors,providing a more natural and convenient way of accessible communication for patients with listening and speaking dysfunction.In this study,a piezoresistive flexible pressure sensor was prepared using a two-dimensional material,MXene,and a highly conductive polymer,poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate)(PEDOT:PSS),as composites,and a stretchable and microstructured ecoflex as a flexible substrate.The piezoresistive sensor demonstrates a high sensitivity of 42.31 kPa~(-1)and fast response(<150 ms)in the pressure range of 0-2.5 kPa,and shows high stability in10000 compression-release cycles.The flexible piezoresistive sensor was attached to the corners of the mouth and captured the muscle movements of the lips,which was combined with a convolutional neural network algorithm to train and test the signals of English words in the Chinese zodiac,with an average accuracy of up to 90.18%.This work increases the versatility of lip recognition systems and lays an important foundation for the direct conversion of lip movement signals into speech or text.

关 键 词：柔性可穿戴电子设备 唇语 柔性压力传感器 MXene PEDOT:PSS 卷积神经网络 

分 类 号：TB332[一般工业技术—材料科学与工程]