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http://dx.doi.org/10.46670/JSST.2022.31.5.301

Cutting-edge Piezo/Triboelectric-based Wearable Physical Sensor Platforms  

Park, Jiwon (Electronic Materials Research Center, Korea Institute of Science and Technology (KIST))
Shin, Joonchul (Electronic Materials Research Center, Korea Institute of Science and Technology (KIST))
Hur, Sunghoon (Electronic Materials Research Center, Korea Institute of Science and Technology (KIST))
Kang, Chong-Yun (Electronic Materials Research Center, Korea Institute of Science and Technology (KIST))
Cho, Kyung-Hoon (School of Materials Science and Engineering, Kumoh National Institute of Technology)
Song, Hyun-Cheol (Electronic Materials Research Center, Korea Institute of Science and Technology (KIST))
Publication Information
Journal of Sensor Science and Technology / v.31, no.5, 2022 , pp. 301-306 More about this Journal
Abstract
With the recent widespread implementation of Internet of Things (IoT) technology driven by Industry 4.0, self-powered sensors for wearable and implantable systems are increasingly gaining attention. Piezoelectric nanogenerators (PENGs) and triboelectric nanogenerators (TENGs), which convert biomechanical energy into electrical energy, can be considered as efficient self-powered sensor platforms. These are energy harvesters that are used as low-power energy sources. However, they can also be used as sensors when an output signal is used to sense any mechanical stimuli. For sensors, collecting high-quality data is important. However, the accuracy of sensing for practical applications is equally important. This paper provides a brief review of the performance advanced by the materials and structures of the latest PENG/TENG-based wearable sensors and intelligent applications applied using artificial intelligence (AI)
Keywords
PENG/TENG-based wearable sensors; Self-powered sensors; Artificial intelligence; Intelligent sensor;
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Times Cited By KSCI : 8  (Citation Analysis)
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