Wang Lu, Su Steven W, Celler Branko G, Chan Gregory S H, Cheng Teddy M, Savkin Andrey V
Human Performance Group, Biomedical Systems Lab, School of Electrical Engineering & Telecommunications, University of New South Wales (UNSW), Sydney, NSW 2052, Australia.
Physiol Meas. 2009 Mar;30(3):227-44. doi: 10.1088/0967-3334/30/3/001. Epub 2009 Feb 6.
This study aims to quantitatively describe the steady-state relationships among percentage changes in key central cardiovascular variables (i.e. stroke volume, heart rate (HR), total peripheral resistance and cardiac output), measured using non-invasive means, in response to moderate exercise, and the oxygen uptake rate, using a new nonlinear regression approach-support vector regression. Ten untrained normal males exercised in an upright position on an electronically braked cycle ergometer with constant workloads ranging from 25 W to 125 W. Throughout the experiment, VO(2) was determined breath by breath and the HR was monitored beat by beat. During the last minute of each exercise session, the cardiac output was measured beat by beat using a novel non-invasive ultrasound-based device and blood pressure was measured using a tonometric measurement device. Based on the analysis of experimental data, nonlinear steady-state relationships between key central cardiovascular variables and VO(2) were qualitatively observed except for the HR which increased linearly as a function of increasing VO(2). Quantitative descriptions of these complex nonlinear behaviour were provided by nonparametric models which were obtained by using support vector regression.
本研究旨在使用一种新的非线性回归方法——支持向量回归，定量描述通过非侵入性手段测量的关键中心心血管变量（即每搏输出量、心率（HR）、总外周阻力和心输出量）的百分比变化之间的稳态关系，这些变化是对适度运动的响应，以及摄氧率。十名未经训练的正常男性在电子制动的自行车测力计上直立运动，工作负荷恒定，范围从25瓦到125瓦。在整个实验过程中，逐次呼吸测定VO₂，逐搏监测心率。在每个运动时段的最后一分钟，使用一种新型的基于超声的非侵入性设备逐搏测量心输出量，并使用眼压测量设备测量血压。基于实验数据分析，除了心率随VO₂增加呈线性增加外，定性观察到关键中心心血管变量与VO₂之间的非线性稳态关系。通过使用支持向量回归获得的非参数模型提供了对这些复杂非线性行为的定量描述。
