Electrode-skin impedance model parameter identification method based on stimulation frequency response

Abstract

The invention discloses an electrode-skin impedance model parameter identification method based on stimulation frequency response. The method is characterized in that resistance and capacitance parameters of the electrode and finger epidermis, finger dermis and subcutaneous tissue are fully considered, an electrode-skin impedance model based on stimulation frequency response is provided for the first time, an improved sine and cosine algorithm is used for identifying parameters of the electrode-skin impedance model, and an accurate electrode-skin impedance model is obtained.

Description

technical field [0001] The invention relates to the parameter identification of a human hand electrode-skin impedance model in an electric stimulation-based tactile feedback device, in particular to a model parameter identification method in an electrode-skin impedance model based on a stimulation frequency response. It is used to construct an accurate force-tactile mapping relationship in the human-computer interaction system to ensure the stability and accuracy of the human-computer interaction electric tactile reproduction control. Background technique [0002] In recent years, tactile reproduction technology has been widely used in human-computer interaction fields such as robots and virtual reality. Due to the advantages of simple structure, fast response and easy control, electrotactile devices have been highly valued by researchers from all walks of life. However, establishing an accurate skin impedance model based on measured stimulus-response data is crucial for ta...

AI Technical Summary

Problems solved by technology

However, most meta-heuristic algorithms cannot balance exploration and development well, and there are problems such as slow convergence speed and easy to fall into local optimum.

[0006] To sum up, it can be seen that the existing human skin impedance circuit model only considers the skin impedance and ignores the influence of the contact between the human fingertip and the electrode array.

Moreover, when establishing a nonlinear skin impedance model, the existing skin impedance model only considers that the nonlinear impedance is related to stimulation time and current.

However, in fact, more studies have shown that human skin impedance is related to the excitation frequency of electrical stimulation; in the identification of skin impedance parameters, traditional mathematical optimization algorithms, such as gradient descent methods, are not suitable for solving highly nonlinear and non-convex problems. The complex optimization problem of

The existing meta-heuristic algorithm can solve such problems well, but there are still problems such as slow convergence and easy to fall into local optimum.

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