College of Life Science and Bio-engineering, Beijing University of Technology, Beijing 100124, China.
College of Life Science and Bio-engineering, Beijing University of Technology, Beijing 100124, China.
Microvasc Res. 2018 Mar;116:20-25. doi: 10.1016/j.mvr.2017.03.008. Epub 2017 Mar 24.
Gaussian modelling method has been reported as a useful method to analyze arterial pulse waveform changes. This study aimed to provide scientific evidence on Gaussian modelling characteristics changes derived from the finger photoplethysmographic (PPG) pulses during exercise and recovery. 65 healthy subjects (18 female and 47 male) were recruited. Finger PPG pulses were digitally recorded with 5 different exercise loads (0, 50, 75, 100, 125W) as well as during each of 4minute (min) recovery period. The PPG pulses were normalized in both width and amplitude for each recording, which were decomposed into three independent Gaussian waves with nine parameters determined, including the peak amplitude (H, H, H), peak time position (N, N, N) and half-width (W, W, W) from each Gaussian wave, and four extended parameters determined, including the peak time interval (T, T) and amplitude ratio (R, R) between 1st Gaussian wave and 2nd, 3rd Gaussian waves. These derived parameters were finally compared between different exercise loads and recovery phases. With gradually increased exercise loads, the peak amplitude H, peak time position N, N, N, and half-width W, W increased, peak amplitude H decreased significantly (all P<0.05). The peak time interval T and T increased significantly from 10.6±1.2 and 36.0±4.4 at rest to 14.4±2.3 and 45.1±6.5 at 100W exercise load, respectively (both P<0.05). The amplitude ratio R increased from 1.07±0.2 at rest to 1.22±0.2 at 100W, and the amplitude ratio R decreased from 1.10±0.3 at rest to 0.42±0.2 at 125W (all P<0.05). An opposite changing trend of these parameters was observed during recovery phases. In conclusion, this study has quantitatively demonstrated significant changes of Gaussian modelling characteristics derived from finger PPG pulse with exercise and during recovery, providing scientific evidence for the physiological mechanism that exercise increases cardiac ejection and vasodilation, and reduces the total peripheral vascular resistance.
高斯建模方法已被报道为分析动脉脉搏波形变化的有用方法。本研究旨在提供来自手指光体积描记(PPG)脉搏在运动和恢复期间的高斯建模特征变化的科学证据。招募了 65 名健康受试者(18 名女性和 47 名男性)。用 5 种不同的运动负荷(0、50、75、100、125W)以及 4 分钟(min)恢复期的每个阶段数字化记录手指 PPG 脉冲。对每个记录的 PPG 脉冲进行宽度和幅度的归一化,将其分解为三个独立的高斯波,确定了九个参数,包括每个高斯波的峰幅度(H、H、H)、峰时间位置(N、N、N)和半宽度(W、W、W),以及四个扩展参数,包括峰时间间隔(T、T)和第一高斯波与第二、第三高斯波之间的幅度比(R、R)。最后比较了不同运动负荷和恢复阶段之间的这些导出参数。随着运动负荷的逐渐增加,峰幅度 H、峰时间位置 N、N、N 和半宽度 W、W 增加,峰幅度 H 显著降低(均 P<0.05)。峰时间间隔 T 和 T 从休息时的 10.6±1.2 和 36.0±4.4 分别显著增加到 100W 运动负荷时的 14.4±2.3 和 45.1±6.5(均 P<0.05)。幅度比 R 从休息时的 1.07±0.2 增加到 100W 时的 1.22±0.2,幅度比 R 从休息时的 1.10±0.3 减少到 125W 时的 0.42±0.2(均 P<0.05)。在恢复阶段观察到这些参数的相反变化趋势。总之,本研究从手指 PPG 脉搏中定量证明了运动和恢复期间高斯建模特征的显著变化,为运动增加心脏射血和血管扩张以及降低总外周血管阻力的生理机制提供了科学证据。