Biomedical Engineering Systems and Technologies
Biomedical Engineering Systems and Technologies
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生物医学工程系统与技术
DOI：
10.1007/978-3-642-29752-6_14
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Samuri S
中科院分区：
文献类型：
--
作者：
Samuri S
电阻抗断层成像（EIT），特别是其在肺部测量中的应用，自20世纪80年代初由Barber和Brown开发以来一直是深入研究的主题。EIT中相对最近的进展之一是绝对EIT系统（aEIT）的开发，其可以估计肺电阻率和相关肺体积的绝对值。在本文中，我们提出了一种基于计算智能（CI）建模的新方法，用于对“电阻率-肺容量”关系进行建模，该方法将允许使用通过谢菲尔德aEIT系统和肺活量计同时测量的来自8名健康志愿者的数据进行更准确的肺容量估计。与原始的谢菲尔德aEIT系统相比，所开发的模型在预测肺体积方面显示出改进的准确性。然而，在“阻力-肺容积”曲线的受试者特异性建模行为中观察到的个体间差异表明，需要模型扩展，由此建模结构自动校准以考虑受试者（或患者特异性）参数间变异性。
Electrical Impedance Tomography (EIT), and in particular its application to pulmonary measurement, has been the subject of intensive research since its development in the early 1980s by Barber and Brown. One of the relatively recent advances in EIT is the development of an absolute EIT system (aEIT) which can estimate absolute values of lung resistivity and associated lung volumes. In this paper we present a new approach based on Computational Intelligence (CI) modelling to model the ‘Resistivity - Lung Volume’ relationship that will allow more accurate lung volume estimations using data from eight (8) healthy volunteers measured simultaneously via the Sheffield aEIT system and a Spirometer. The developed models show an improved accuracy in the prediction of lung volumes, as compared with the original Sheffield aEIT system. However the inter-individual differences observed in the subject-specific modelling behaviour of the ‘Resistivity-Lung Volume’ curves suggest that a model extension is needed, whereby the modelling structure auto-calibrates to account for subject (or patient-specific) inter-parameter variability.