A Wireless Intelligent Motion Correction System for Skating Monitoring Based on a Triboelectric Nanogenerator
Smart sport and big data have become inextricably linked with new technologies and devices to monitor sport-related information in real time. In this paper, a lightweight, portable and self-powered triboelectric nanogenerator (LPS-TENG) has been developed to monitor the frequency and force of skater...
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Veröffentlicht in: | Electronics (Basel) 2023-01, Vol.12 (2), p.320 |
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Sprache: | eng |
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Zusammenfassung: | Smart sport and big data have become inextricably linked with new technologies and devices to monitor sport-related information in real time. In this paper, a lightweight, portable and self-powered triboelectric nanogenerator (LPS-TENG) has been developed to monitor the frequency and force of skaters’ pedaling. Friction layers are formed of polytetrafluoroethylene (PTFE) and nylon films. Based on the triboelectric effect, LPS-TENG does not require an external power supply, and it can be used to monitor biomechanical motion independently. Under the conditions of 1 Hz and 17.19 N, the outputting voltage of LPS-TENG is stabilized at 14 V. Wireless data transmission is achieved with the help of the LPS-TENG and AD module. Visual feedback is provided by the upper computer system in the process of processing data. The wireless intelligent motion correction system is composed of an LPS-TENG, an AD module and a back-end computer. It can clearly analyze the changes between different frequencies and forces during skating. Results showed that the signal of tester’s high-frequency and great-force motion, was transmitted to the computer, and its feedback was given after analysis and processing successfully. The system may help coaches develop training methods, means and tactics to increase athletes’ performance and competitive level in athletic sport. The purpose of this study is to provide new ideas for monitoring skaters’ sport techniques, promote the use of force sensors in the monitoring of sport and develop intelligent assistant training systems. |
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ISSN: | 2079-9292 2079-9292 |
DOI: | 10.3390/electronics12020320 |