从视频中稳健有效地估计心率脉搏。
Robust efficient estimation of heart rate pulse from video.
作者信息
Xu Shuchang, Sun Lingyun, Rohde Gustavo Kunde
机构信息
Department of Information Science and Engineering, Hangzhou Normal University, Hangzhou, 311121, China ; Center for Bioimage Informatics, Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, 15213, USA.
Department of Computer Science, Zhejiang University, Hangzhou, China , 310058.
出版信息
Biomed Opt Express. 2014 Mar 10;5(4):1124-35. doi: 10.1364/BOE.5.001124. eCollection 2014 Apr 1.
We describe a simple but robust algorithm for estimating the heart rate pulse from video sequences containing human skin in real time. Based on a model of light interaction with human skin, we define the change of blood concentration due to arterial pulsation as a pixel quotient in log space, and successfully use the derived signal for computing the pulse heart rate. Various experiments with different cameras, different illumination condition, and different skin locations were conducted to demonstrate the effectiveness and robustness of the proposed algorithm. Examples computed with normal illumination show the algorithm is comparable with pulse oximeter devices both in accuracy and sensitivity.
我们描述了一种简单而强大的算法，用于实时从包含人体皮肤的视频序列中估计心率脉搏。基于光与人体皮肤相互作用的模型，我们将动脉搏动引起的血液浓度变化定义为对数空间中的像素商，并成功地将导出的信号用于计算脉搏心率。进行了各种不同相机、不同光照条件和不同皮肤位置的实验，以证明所提算法的有效性和鲁棒性。在正常光照下计算的示例表明，该算法在准确性和灵敏度方面与脉搏血氧仪设备相当。
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