Department of Biomedical Engineering, Furtwangen University, Jakob-Kienzle Straße 17, D-78054, Villingen-Schwenningen, Germany.
Physiol Meas. 2012 Jan;33(1):51-64. doi: 10.1088/0967-3334/33/1/51. Epub 2011 Dec 7.
The objective of this paper is to introduce and evaluate the adaptive SLICE method (ASM) for continuous determination of intratidal nonlinear dynamic compliance and resistance. The tidal volume is subdivided into a series of volume intervals called slices. For each slice, one compliance and one resistance are calculated by applying a least-squares-fit method. The volume window (width) covered by each slice is determined based on the confidence interval of the parameter estimation. The method was compared to the original SLICE method and evaluated using simulation and animal data. The ASM was also challenged with separate analysis of dynamic compliance during inspiration. If the signal-to-noise ratio (SNR) in the respiratory data decreased from +∞ to 10 dB, the relative errors of compliance increased from 0.1% to 22% for the ASM and from 0.2% to 227% for the SLICE method. Fewer differences were found in resistance. When the SNR was larger than 40 dB, the ASM delivered over 40 parameter estimates (42.2 ± 1.3). When analyzing the compliance during inspiration separately, the estimates calculated with the ASM were more stable. The adaptive determination of slice bounds results in consistent and reliable parameter values. Online analysis of nonlinear respiratory mechanics will profit from such an adaptive selection of interval size.
本文旨在介绍并评估自适应 SLICE 方法(ASM),用于连续测定潮汐内非线性动态顺应性和阻力。潮气量被细分为一系列体积区间,称为切片。对于每个切片,通过应用最小二乘法计算一个顺应性和一个阻力。每个切片所覆盖的体积窗口(宽度)基于参数估计的置信区间来确定。该方法与原始 SLICE 方法进行了比较,并使用模拟和动物数据进行了评估。ASM 还在吸气过程中对动态顺应性进行了单独分析。如果呼吸数据中的信噪比(SNR)从+∞下降到 10 dB,顺应性的相对误差从 ASM 的 0.1%增加到 22%,从 SLICE 方法的 0.2%增加到 227%。阻力的差异较小。当 SNR 大于 40 dB 时,ASM 提供了超过 40 个参数估计值(42.2±1.3)。当单独分析吸气过程中的顺应性时,ASM 计算出的估计值更稳定。切片边界的自适应确定可产生一致且可靠的参数值。这种间隔大小的自适应选择将使在线分析非线性呼吸力学受益。