Flexible Wide-Range Triboelectric Sensor for Physiological Signal Monitoring and Human Motion Recognition Flexible Wide-Range Triboelectric Sensor for Physiological Signal Monitoring and Human Motion Recognition AITranslate
Abstract AITranslate
Triboelectric nanogenerators, as a device that converts mechanical energy into electrical energy, can respond to external pressure stimuli. However, most triboelectric sensors can only perform pressure measurements in a narrow pressure range, which limits their application in multiple scenarios. Here, we proposed a wide-range triboelectric pressure sensor based on the difference in Young’s modulus of the materials and a double-sandwich-structure design. We analyzed the effect of the structural angle at the material surface on the sensor performance and obtained an optimal combination of angles for a double-sandwich-structure sensor. The proposed sensor has outstanding performance including high sensitivity (249.32 mV/kPa), wide range (0–450 kPa), and fast response time (26 ms). Meanwhile, the sensor has a quite low detection limit (8.72 Pa). The designed sensor can be applied not only to the detection of small physiological signals but also to large plantar pressure sensing. A human motion recognition system based on plantar pressure was developed. Moreover, we also designed a convolutional gated recurrent unit model to recognize four human motions with high accuracy (99.42%). This work provides a design idea to extend the range of the triboelectric sensor to meet multiple applications.
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DOI:https://doi.org/10.1021/acsaelm.2c00681
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Triboelectric nanogenerators, as a device that converts mechanical energy into electrical energy, can respond to external pressure stimuli. However, most triboelectric sensors can only perform pressure measurements in a narrow pressure range, which limits their application in multiple scenarios. Here, we proposed a wide-range triboelectric pressure sensor based on the difference in Young’s modulus of the materials and a double-sandwich-structure design. We analyzed the effect of the structural angle at the material surface on the sensor performance and obtained an optimal combination of angles for a double-sandwich-structure sensor. The proposed sensor has outstanding performance including high sensitivity (249.32 mV/kPa), wide range (0–450 kPa), and fast response time (26 ms). Meanwhile, the sensor has a quite low detection limit (8.72 Pa). The designed sensor can be applied not only to the detection of small physiological signals but also to large plantar pressure sensing. A human motion recognition system based on plantar pressure was developed. Moreover, we also designed a convolutional gated recurrent unit model to recognize four human motions with high accuracy (99.42%). This work provides a design idea to extend the range of the triboelectric sensor to meet multiple applications.
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| GB/T 7714-2015 | [1] Ran Xu, Fangyuan Luo, Zhiyuan Zhu, et al. ACS Applied Electronic Materials, 2022(4). DOI:10.1021/acsaelm.2c00681. |
| MLA | [1] Ran Xu, et al., ACS Applied Electronic Materials, no. 4, 2022, https://doi.org/10.1021/acsaelm.2c00681. |
| APA | [1] Ran Xu, Fangyuan Luo, Zhiyuan Zhu, Mintong Li, & Bin Chen. (2022). ACS Applied Electronic Materials(4). https://doi.org/10.1021/acsaelm.2c00681 |
| IEEE | [1] Ran Xu, Fangyuan Luo, Zhiyuan Zhu, Mintong Li, and Bin Chen, ACS Applied Electronic Materials, no. 4, 2022, doi: 10.1021/acsaelm.2c00681. keywords: {triboelectric nanogenerator selfpowered sensor motion recognition health monitoring deep learning} |
