Suppr超能文献

用于电阻抗光谱仪的组织阻抗模型参数实时提取

Real-time extraction of tissue impedance model parameters for electrical impedance spectrometer.

作者信息

Kun S, Ristic B, Peura R A, Dunn R M

机构信息

Worcester Polytechnic Institute, Biomedical Engineering Department, MA 01609, USA.

出版信息

Med Biol Eng Comput. 1999 Jul;37(4):428-32. doi: 10.1007/BF02513325.

Abstract

This paper presents a new algorithm for real-time extraction of tissue electrical impedance model parameters from in vivo electrical impedance spectroscopic measurements. This algorithm was developed as a part of a system for muscle tissue ischemia measurements using electrical impedance spectroscopy. An iterative least square fitting method, biased with a priori knowledge of the impedance model was developed. It simultaneously uses both the real and imaginary impedance spectra to calculate tissue parameters R0, R infinity, alpha and tau. The algorithm was tested with simulated data, and during real-time in vivo ischemia experiments. Experimental results were achieved with standard deviations of sigma R0 = 0.80%, sigma R infinity = 0.84%, sigma alpha = 0.72%, and sigma tau = 1.26%. On a Pentium II based PC, the algorithm converges to within 0.1% of the results in 17 ms. The results show that the algorithm possesses excellent parameter extraction capabilities, repeatability, speed and noise rejection.

摘要

本文提出了一种用于从体内电阻抗光谱测量中实时提取组织电阻抗模型参数的新算法。该算法是作为使用电阻抗光谱进行肌肉组织缺血测量系统的一部分而开发的。开发了一种基于阻抗模型先验知识的迭代最小二乘拟合方法。它同时使用实部和虚部阻抗谱来计算组织参数R0、R∞、α和τ。该算法用模拟数据进行了测试,并在实时体内缺血实验中进行了测试。实验结果的标准差为σR0 = 0.80%,σR∞ = 0.84%,σα = 0.72%,στ = 1.26%。在基于奔腾II的个人计算机上,该算法在17毫秒内收敛到结果的0.1%以内。结果表明,该算法具有出色的参数提取能力、重复性、速度和抗噪声能力。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验