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Bubbles-Induced Porous Structure-Based Flexible Piezoresistive Sensors for Speech Recognition.
Gao, Xiaoguang; Yuan, Lin; Xue, Chengzhen; Zhang, Xiaoliang; Meng, Xuejuan; Li, Xiaochun.
Afiliación
  • Gao X; Institute of Biomedical Precision Testing and Instrumentation, College of Biomedical Engineering, Taiyuan University of Technology, Taiyuan 030024, China.
  • Yuan L; Institute of Biomedical Precision Testing and Instrumentation, College of Biomedical Engineering, Taiyuan University of Technology, Taiyuan 030024, China.
  • Xue C; Institute of Biomedical Precision Testing and Instrumentation, College of Biomedical Engineering, Taiyuan University of Technology, Taiyuan 030024, China.
  • Zhang X; Institute of Biomedical Precision Testing and Instrumentation, College of Biomedical Engineering, Taiyuan University of Technology, Taiyuan 030024, China.
  • Meng X; Institute of Biomedical Precision Testing and Instrumentation, College of Biomedical Engineering, Taiyuan University of Technology, Taiyuan 030024, China.
  • Li X; Institute of Biomedical Precision Testing and Instrumentation, College of Biomedical Engineering, Taiyuan University of Technology, Taiyuan 030024, China.
ACS Appl Mater Interfaces ; 16(7): 9532-9543, 2024 Feb 21.
Article en En | MEDLINE | ID: mdl-38345942
ABSTRACT
Flexible piezoresistive sensors with a porous structure that are used in the field of speech recognition are seldom characterized by both high sensitivity and ease of preparation. In this study, a piezoresistive sensor with a porous structure that is both highly sensitive and can be prepared by using a simple method is proposed for speech recognition. The preparation process utilizes the interaction of bubbles generated by ethanol evaporation and active agents with polydimethylsiloxane to produce a porous flexible substrate. This preparation process requires neither templates nor harsh experimental conditions such as a low temperature and a low pressure. Furthermore, the prepared piezoresistive sensor has excellent properties, such as a high sensitivity (27.6 kPa-1), a satisfactory response time (800 µs), and a good stability (10,000 cycles). When used for speech recognition, more than 1500 vocalizations and silent speech signals obtained from subjects saying numbers from "0" to "9" were collected by the sensor for training a convolutional neural network model. The average accuracy of the recognition reached 94.8%. The simple preparation process and the excellent performance of the prepared flexible piezoresistive sensor endow it with a wide application prospect in the field of speech recognition.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Habla / Percepción del Habla Límite: Humans Idioma: En Revista: ACS Appl Mater Interfaces Asunto de la revista: BIOTECNOLOGIA / ENGENHARIA BIOMEDICA Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Habla / Percepción del Habla Límite: Humans Idioma: En Revista: ACS Appl Mater Interfaces Asunto de la revista: BIOTECNOLOGIA / ENGENHARIA BIOMEDICA Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos