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• W3012214704 endingPage "155014772090544" @default.
• W3012214704 startingPage "155014772090544" @default.
• W3012214704 abstract "Gait analysis has become a hot spot in recent years, because it is proven that the status of a vast number of chronic diseases can be reflected by changes in gait. Furthermore, gait analysis can also help in improving the performance of athletes. Among the diverse gait analysis techniques, the piezoelectric-based insole technique has received broad attention due to its merits such as passive detection, high sensitivity, and low power consumption. However, the key coefficient of detecting plantar normal stress, the piezoelectric d 33 coefficient, relies on the force frequency, which occupies a relatively wide bandwidth (1 Hz–1 kHz) during walking events. In order to get the frequency information of the signal, in this work, empirical mode decomposition is used to separate the gait signal into several intrinsic mode functions, and then the frequency information of each function is interpreted using the normalized Hilbert transform. In this way, the piezoelectric d 33 coefficient is calibrated at every moment, obtaining higher accuracy (2.65% maximum improvement) in gait signal detection, promoting the development of gait analysis–based disease diagnosis and treatment." @default.
• W3012214704 created "2020-03-23" @default.
• W3012214704 creator A5002187135 @default.
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• W3012214704 date "2020-03-01" @default.
• W3012214704 modified "2023-10-12" @default.
• W3012214704 title "A force–voltage responsivity stabilization method for piezoelectric-based insole gait analysis for high detection accuracy in health monitoring" @default.
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• W3012214704 doi "https://doi.org/10.1177/1550147720905441" @default.
• W3012214704 hasPublicationYear "2020" @default.
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