4.8 Article

Scalable, stretchable and washable triboelectric fibers for self-powering human-machine interaction and cardiopulmonary resuscitation training

Journal

NANO ENERGY
Volume 102, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.nanoen.2022.107737

Keywords

Fiber-shaped triboelectric nanogenerators; Motion detection; Human-machine interaction; Cardiopulmonary resuscitation; Self-powering

Funding

  1. Austrian Research Promotion Agency (FFG) [875643/GJHZ2046]
  2. Chinese Academy of Sciences (CAS)
  3. National Natural Science Foundation of China [61871368, 62122080]
  4. Natural Science Foundation of Shanghai
  5. Shanghai Pujiang Program [21PJ1414800]

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A scalable, flexible and washable fiber-shaped triboelectric nanogenerator has been developed with excellent mechanical stretchability and electrical output performance. It can harvest human mechanical energy as a self-powered sensor for the detection of physiological signals and human-machine interactions, and can be used in a cardiopulmonary resuscitation training system to evaluate compression quality.
Flexible and stretchable fiber-shaped triboelectric nanogenerators (FTENGs) have been extensively investigated in wearable electronics due to their ability to harvest human-body mechanical energy and serve as self-powered sensing systems. However, developing a facial and scalable fabrication method for highly flexible and comfortable FTENGs remains a formidable challenge. Here, a scalable, flexible and washable coaxially structured FTENGs is developed, which possess excellent mechanical stretchability, weave-ability and electrical output performance. The instantaneous power density of FTENG fabrics with an effective area of 32 cm2 can reach as high as 0.957 W m-2 under an external load resistance of 10 M omega, which is superior to the vast majority of re-ported work. As self-powered sensors, FTENGs can harvest human motion energy for the detection of body physiological signals and human-machine interactions. Importantly, a wearable cardiopulmonary resuscitation training system is developed based on the FTENGs, which can evaluate the quality of chest compressions, including compression rate, depth, chest compression leaning and chest recoil condition. All these advantages of FTENGs are expected to broadly benefit the development of medical assistance training.

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