Selected article for: "deep learning and high sensitivity"

Author: Liu, Zekun Li Zhenhong Zhai Heng Jin Lu Chen Kaili Yi Yangpeiqi Gao Yuan Xu Lulu Zheng Yan Yao Sirui Liu Zhangchi Li Gang Song Qingwen Yue Pengfei Xie Shengquan Li Yi Zheng Zijian
Title: A highly sensitive stretchable strain sensor based on multi-functionalized fabric for respiration monitoring and identification
  • Cord-id: o19yutnt
  • Document date: 2021_1_1
  • ID: o19yutnt
    Snippet: Wearable strain sensors have generated considerable recent research interest due to their huge potential in the real-time detection of human body deformation. State-of-the-art strain sensors are normally fabricated through conductive networks with a single sensing element, which always faces the challenge of either limited stretchability or inferior quality in sensitivity. In this work, we report a highly sensitive strain sensor based on a multi-functionalized fabric through carbonization and po
    Document: Wearable strain sensors have generated considerable recent research interest due to their huge potential in the real-time detection of human body deformation. State-of-the-art strain sensors are normally fabricated through conductive networks with a single sensing element, which always faces the challenge of either limited stretchability or inferior quality in sensitivity. In this work, we report a highly sensitive strain sensor based on a multi-functionalized fabric through carbonization and polymer-assisted copper deposition. The sensor shows high sensitivity (Gauge factor∼3557.6 in the strain range from 0 to 48%), and outstanding stretchability up to the strain of 300%, which is capable of detecting different types of deformation of the human body. By integrating the high-performance sensor with a deep learning network, we demonstrate a high accuracy of respiration monitoring and emergency alarm system, showing the enormous application potential of the sensor in personal and public healthcare.

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