A Machine Learning-Combined Flexible Sensor for Tactile Detection and Voice Recognition

作者：Jiawang Xie, Yuzhi Zhao, Dezhi Zhu, Jianfeng Yan, Jiaqun Li, Ming Qiao, Guangzhi He, Shengfa Deng · 发表于：ACS Applied Materials & Interfaces · 年份：2023 · DOI：10.1021/acsami.2c22287 · 被引用次数：86 · 研究领域：Advanced Sensor and Energy Harvesting Materials、Tactile and Sensory Interactions、Innovative Energy Harvesting Technologies

Intelligent sensors have attracted substantial attention for various applications, including wearable electronics, artificial intelligence, healthcare monitoring, and human-machine interactions. However, there still remains a critical challenge in developing a multifunctional sensing system for complex signal detection and analysis in practical applications. Here, we develop a machine learning-combined flexible sensor for real-time tactile sensing and voice recognition through laser-induced graphitization. The intelligent sensor with a triboelectric layer can convert local pressure to an electrical signal through a contact electrification effect without external bias, which has a characteristic response behavior when exposed to various mechanical stimuli. With the special patterning design, a smart human-machine interaction controlling system composed of a digital arrayed touch panel is constructed to control electronic devices. Based on machine learning, the real-time monitoring and recognition of the changes of voice are achieved with high accuracy. The machine learning-empowered flexible sensor provides a promising platform for the development of flexible tactile sensing, real-time health detection, human-machine interaction, and intelligent wearable devices.