Method for parameter estimation of human skin-electrode bioelectrical impedance model based on electrical tactile device
A method for parameter estimation of a human skin-electrode bioelectrical impedance model based on an electrical tactile device is provided. The method is characterized in that: the recursive algorithm with forgetting factor is used, and the data is weighted with the default forgetting factor, so th...
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creator | LIN FANCHAO LI CHUNQUAN ZHANG HAO SUO JINGWEN XIONG HUI LUO ZU YANG FENG |
description | A method for parameter estimation of a human skin-electrode bioelectrical impedance model based on an electrical tactile device is provided. The method is characterized in that: the recursive algorithm with forgetting factor is used, and the data is weighted with the default forgetting factor, so that the new data occupies a greater weight in the parameter estimation; the new input and output dataprovided by the electrical tactile device are used to improve the estimation accuracy, and when the parameters are changed, the estimation is modified to realize online real-time estimation of the parameters; and at the same time, the augmented model is adopted, and the error between the electrical stimulus amount output by the complete and reasonable hypothesis model and the real finger electrical stimulus amount is colored noise, but not the ideal white noise, so that the result is more in line with the actual situation and can adapt to parameter estimation in different noise conditions. The method provided by the |
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The method is characterized in that: the recursive algorithm with forgetting factor is used, and the data is weighted with the default forgetting factor, so that the new data occupies a greater weight in the parameter estimation; the new input and output dataprovided by the electrical tactile device are used to improve the estimation accuracy, and when the parameters are changed, the estimation is modified to realize online real-time estimation of the parameters; and at the same time, the augmented model is adopted, and the error between the electrical stimulus amount output by the complete and reasonable hypothesis model and the real finger electrical stimulus amount is colored noise, but not the ideal white noise, so that the result is more in line with the actual situation and can adapt to parameter estimation in different noise conditions. 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The method is characterized in that: the recursive algorithm with forgetting factor is used, and the data is weighted with the default forgetting factor, so that the new data occupies a greater weight in the parameter estimation; the new input and output dataprovided by the electrical tactile device are used to improve the estimation accuracy, and when the parameters are changed, the estimation is modified to realize online real-time estimation of the parameters; and at the same time, the augmented model is adopted, and the error between the electrical stimulus amount output by the complete and reasonable hypothesis model and the real finger electrical stimulus amount is colored noise, but not the ideal white noise, so that the result is more in line with the actual situation and can adapt to parameter estimation in different noise conditions. 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The method is characterized in that: the recursive algorithm with forgetting factor is used, and the data is weighted with the default forgetting factor, so that the new data occupies a greater weight in the parameter estimation; the new input and output dataprovided by the electrical tactile device are used to improve the estimation accuracy, and when the parameters are changed, the estimation is modified to realize online real-time estimation of the parameters; and at the same time, the augmented model is adopted, and the error between the electrical stimulus amount output by the complete and reasonable hypothesis model and the real finger electrical stimulus amount is colored noise, but not the ideal white noise, so that the result is more in line with the actual situation and can adapt to parameter estimation in different noise conditions. The method provided by the</abstract><oa>free_for_read</oa></addata></record> |
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title | Method for parameter estimation of human skin-electrode bioelectrical impedance model based on electrical tactile device |
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