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使用近红外反射光谱法在运动期间对静脉血pH值进行无创体内测量。

Noninvasive in vivo measurement of venous blood pH during exercise using near-infrared reflectance spectroscopy.

作者信息

Yang Ye, Soyemi Olusola O, Landry Michelle R, Soller Babs R

机构信息

Department of Anesthesiology, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, Massachusetts 01655, USA.

出版信息

Appl Spectrosc. 2007 Feb;61(2):223-9. doi: 10.1366/000370207779947657.

Abstract

Blood pH is an important indicator of anaerobic metabolism in exercising muscle. This paper demonstrates multivariate calibration techniques that can be used to produce a general pH model that can be applied to spectra from any new subject without significant prediction error. Tissue spectra (725 approximately 880 nm) were acquired through the skin overlying the flexor digitorum profundus muscle on the forearms of eight healthy subjects during repetitive hand-grip exercise and referenced to the pH of venous blood drawn from a catheter placed in a vein close to the muscle. Calibration models were developed using multi-subject partial least squares (PLS) and validated using subject-out cross-validation after the subject-to-subject spectral variations were corrected by mathematical preprocessing methods. A combination of standard normal variate (SNV) scaling and principal component analysis loading correction (PCALC) successfully removed most of the subject-to-subject variations and provided the most accurate prediction results.

摘要

血液pH值是运动肌肉中无氧代谢的重要指标。本文展示了多元校准技术,这些技术可用于生成一个通用的pH模型,该模型可应用于任何新受试者的光谱,且预测误差不大。在八名健康受试者进行重复性握力运动期间,通过覆盖在前臂指深屈肌上的皮肤获取组织光谱(725至880纳米),并以从置于靠近该肌肉的静脉中的导管抽取的静脉血的pH值为参考。使用多受试者偏最小二乘法(PLS)建立校准模型,并在通过数学预处理方法校正受试者间光谱变化后,使用留一法交叉验证进行验证。标准正态变量(SNV)缩放和主成分分析载荷校正(PCALC)的组合成功消除了大部分受试者间的变化,并提供了最准确的预测结果。

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