4.8 Article

Weaved piezoresistive triboelectric nanogenerator for human motion monitoring and gesture recognition

Journal

NANO ENERGY
Volume 96, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.nanoen.2022.107135

Keywords

Triboelectric nanogenerator; Piezoresistive fiber; Multimodal sensing

Funding

  1. National Key R&D Project from Ministry of Science and Technology, China [2016YFA0202702, 2016YFA0202701]
  2. National Natural Science Foundation of China (NSFC) [51873020]

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This study presents a piezoresistive fiber-based triboelectric sensor with a hierarchical structure for sensitive detection of stress, strain, and the mass and position of touched objects. The sensor holds great potential in personal health monitoring and human-computer interaction.
Self-powered tactile sensors based on triboelectric nanogenerators (TENGs) can be sustainable and intelligent for dynamically monitoring various physiological signals and motions. Nevertheless, it is still very challenging for the TENG-based sensors to be simultaneously sensitive to deformation caused by stress and strain. Herein, a piezoresistive fiber-base triboelectric sensor (PRF-TES) is designed by using nylon thread, silver nanowires (Ag NWs), carbon nanotubes (CNTs), Parafilm and polydimethylsiloxane (PDMS) as source materials. The elaborate hierarchical structure of the textile PRF-TES ranges from one-dimensional macroscopic fibers to elastic polymer with an internal nanoscale CNTs percolation network, which presents a relatively large contact area, multiple contact points and large deformation space for both mechanical energy collection and force sensing. Dynamically, the textile TENG enables the monitoring of physically changes of human body (for example, joint movement, gesture, etc.), but also the information on the contacted object, such as material texture, type and shape. Statically, it can sensitively detect the stress and strain itself as well as the mass and position of the touched object in the two-dimensional space. This work enlightens the development of highly sensitive and multimodal sensors for broad application in personal health monitoring and human-computer interaction.

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