Recent Advances in Self-Powered Wearable Sensors Based on Piezoelectric and Triboelectric Nanogenerators

Biosensors (Basel). 2022 Dec 27;13(1):37. doi: 10.3390/bios13010037.


Early clinical diagnosis and treatment of disease rely heavily on measuring the many various types of medical information that are scattered throughout the body. Continuous and accurate monitoring of the human body is required in order to identify abnormal medical signals and to locate the factors that contribute to their occurrence in a timely manner. In order to fulfill this requirement, a variety of battery-free and self-powered methods of information collecting have been developed. For the purpose of a health monitoring system, this paper presents smart wearable sensors that are based on triboelectric nanogenerators (TENG) and piezoelectric nanogenerators (PENG), as well as hybrid nanogenerators that combine piezoelectric and triboelectric nanogenerators (PTNG). Following the presentation of the PENG and TENG principles, a summary and discussion of the most current developments in self-powered medical information sensors with a variety of purposes, structural designs, and electric performances follows. Wearable sensors that generate their own electricity are crucial not only for the proper development of children and patients with unique conditions, but for the purpose of maintaining checks on the wellbeing of the elderly and those who have recently recovered from illness, and for administering any necessary medical care. This work sought to do two things at once: provide perspectives for health monitoring, and open up new avenues for the analysis of long-distance biological movement status.

Keywords: piezoelectric nanogenerators (PENG); self-powered wearable sensors; triboelectric nanogenerators (TENG).

Publication types

  • Review

MeSH terms

  • Aged
  • Child
  • Electric Power Supplies*
  • Electricity
  • Humans
  • Wearable Electronic Devices*

Grants and funding

This work was supported by the funding of the Guangdong Provincial Research Platform and Project under No. 2022KQNCX233, the Foundation of State Key Laboratory of Public Big Data under No. PBD2022-14, the Science and Technology Ph.D. Research Startup Project under Grant No. SZIIT2022KJ001, and the Shenzhen University Stability Support Program under No. 20220820003203001.