PDF(Pubmed)
Abstract：
In recent years, hypertension has become one of the leading causes of illness and death worldwide. Changes in lifestyle among the population have led to an increasing prevalence of hypertension. This study proposes a non-contact blood pressure estimation method that allows patients to conveniently monitor their blood pressure values. By utilizing a webcam to track facial features and the region of interest (ROI) for obtaining forehead images, independent component analysis (ICA) is employed to eliminate artifact signals. Subsequently, physiological parameters are calculated using the principle of optical wave reflection. The Nelder-Mead (NM) simplex method is combined with the particle swarm optimization (PSO) algorithm to optimize the empirical parameters, thus enhancing computational efficiency and accurately determining the optimal solution for blood pressure estimation. The influences of light intensity and camera distance on the experimental results are also discussed. Furthermore, the measurement time is only 10 s. The superior accuracy and efficiency of the proposed methodology are demonstrated by comparing them with those in other published literature.
摘要：
近年来,高血压已成为全球疾病和死亡的主要原因之一。人群中生活方式的改变导致高血压患病率增加。这项研究提出了一种非接触式血压估算方法，该方法使患者可以方便地监测其血压值。通过利用网络摄像头来跟踪面部特征和感兴趣区域（ROI）以获取前额图像，采用独立分量分析(ICA)来消除伪影信号。随后，利用光波反射原理计算生理参数。Nelder-Mead(NM)单纯形法与粒子群优化(PSO)算法相结合,对经验参数进行优化,从而提高计算效率，准确确定血压估计的最优解。还讨论了光照强度和相机距离对实验结果的影响。此外，测量时间仅为10s。通过与其他已发表文献中的方法进行比较，证明了所提出方法的优越精度和效率。
