Wang Boshuo, Weiland James D
IEEE Trans Biomed Eng. 2016 Oct;63(10):2086-2094. doi: 10.1109/TBME.2015.2510335. Epub 2015 Dec 17.
This study analyzes the peak resistance frequency (PRF) method described by Mercanzini et al., a method that can easily extract the tissue resistance from impedance spectroscopy for many neural engineering applications but has no analytical description thus far.
Mathematical analyses and computer simulations were used to explore underlying principles, accuracy, and limitations of the PRF method.
The mathematical analyses demonstrated that the PRF method has an inherent but correctable deviation dependent on the idealness of the electrode-tissue interface, which is validated by simulations. Further simulations show that both frequency sampling and noise affect the accuracy of the PRF method, and in general, it performs less accurately than least squares methods. However, the PRF method achieves simplicity and reduced measurement and computation time at the expense of accuracy.
From the qualitative results, the PRF method can work with reasonable precision and simplicity, although its limitation and the idealness of the electrode-tissue interface involved should be taken into consideration.
This paper provides a mathematical foundation for the PRF method and its practical implementation.
本研究分析了梅尔坎齐尼等人描述的峰值电阻频率（PRF）方法，该方法可轻松从阻抗谱中提取组织电阻，适用于许多神经工程应用，但迄今为止尚无解析描述。
采用数学分析和计算机模拟来探究PRF方法的基本原理、准确性和局限性。
数学分析表明，PRF方法存在与电极 - 组织界面理想程度相关的固有但可校正的偏差，这一点通过模拟得到了验证。进一步的模拟表明，频率采样和噪声都会影响PRF方法的准确性，总体而言，其准确性低于最小二乘法。然而，PRF方法以牺牲准确性为代价实现了简单性，并减少了测量和计算时间。
从定性结果来看，PRF方法可以在合理的精度和简单性下工作，不过应考虑其局限性以及所涉及的电极 - 组织界面的理想程度。
本文为PRF方法及其实际应用提供了数学基础。
