<p>Flexible pressure sensors are key components of Internet of Things systems for monitoring environmental and physiological signals, yet simultaneously achieving a&#xa0;high sensitivity, a&#xa0;fast response&#xa0;time, and a&#xa0;high mechanical&#xa0;durability remains challenging owing to the lack of sophisticated structural designs that balance sensing performance and robustness. Here, we demonstrate a multiscale artificial spider web (MASW) fabricated via copper-mesh-assisted electrospinning of biodegradable polylactic acid, forming a nanofiber network that efficiently transmits stress while enhancing mechanical stability. The resulting pressure&#xa0;sensor simultaneously shows a&#xa0;high sensitivity of 39.85 [kPa]<sup>−1</sup>,&#xa0;a&#xa0;fast response of 42 ms and&#xa0;high durability over 6000 loading cycles, enabling reliable and versatile neural-network-assisted real-time monitoring of multiple physiological signals, including pulse, breathing, and vocalization. Furthermore, leveraging precise joint movement signal acquisition, a human-machine interaction system was developed with potential applications in fine motor rehabilitation for Parkinson’s disease, suggesting strong promise for sustainable healthcare and IoT systems.</p>

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Multiscale artificial spider web for comprehensive pressure sensing and human-machine interaction

  • Jing Dai,
  • Kwan-Nyeong Kim,
  • Guangzhong Xie,
  • Dong-Su Choi,
  • Seung-Woo Lee,
  • Eojin Yoon,
  • Chan-Yul Park,
  • Han Dai,
  • Somin Kim,
  • Hyun-Haeng Lee,
  • Tae-Woo Lee

摘要

Flexible pressure sensors are key components of Internet of Things systems for monitoring environmental and physiological signals, yet simultaneously achieving a high sensitivity, a fast response time, and a high mechanical durability remains challenging owing to the lack of sophisticated structural designs that balance sensing performance and robustness. Here, we demonstrate a multiscale artificial spider web (MASW) fabricated via copper-mesh-assisted electrospinning of biodegradable polylactic acid, forming a nanofiber network that efficiently transmits stress while enhancing mechanical stability. The resulting pressure sensor simultaneously shows a high sensitivity of 39.85 [kPa]−1, a fast response of 42 ms and high durability over 6000 loading cycles, enabling reliable and versatile neural-network-assisted real-time monitoring of multiple physiological signals, including pulse, breathing, and vocalization. Furthermore, leveraging precise joint movement signal acquisition, a human-machine interaction system was developed with potential applications in fine motor rehabilitation for Parkinson’s disease, suggesting strong promise for sustainable healthcare and IoT systems.