A novel method for in-situ extracting bio-impedance model parameters optimized for embedded hardware

A novel method for embedded hardware-based parameter estimation of the Cole model of bioimpedance is developed and presented. The model parameters R-infinity, R-1 and C are estimated using the derived set of equations based on measured values of real (R) and imaginary part (X) of bioimpedance, as well as the numerical approximation of the first derivative of quotient R/X with respect to angular frequency. The optimal value for parameter alpha is estimated using a brute force method. The estimation accuracy of the proposed method is very similar with the relevant work from the existing literature. Moreover, performance evaluation was performed using the MATLAB software installed on a laptop, as well as on the three embedded-hardware platforms (Arduino Mega2560, Raspberry Pi Pico and XIAO SAMD21). Obtained results showed that the used platforms can perform reliable bioimpedance processing with the same accuracy, while Raspberry Pi Pico is the fastest solution with the smallest energy consumption.

Automated summary

A novel method for embedded hardware-based parameter estimation of the Cole model of bioimpedance is proposed in this study. The method utilizes a set of derived equations based on measured values of bioimpedance and the numerical approximation of the first derivative of quotient R/X with respect to angular frequency. The accuracy of the proposed method is comparable to existing literature, and performance evaluation is conducted on different embedded-hardware platforms. The results show that Raspberry Pi Pico performs the fastest and with the least energy consumption.