使用主成分分析进行动态心率估计。
Dynamic heart rate estimation using principal component analysis.
作者信息
Yu Yong-Poh, Raveendran P, Lim Chern-Loon, Kwan Ban-Hoe
机构信息
Department of Electrical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia ;
Department of Electrical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia.
出版信息
Biomed Opt Express. 2015 Oct 29;6(11):4610-8. doi: 10.1364/BOE.6.004610. eCollection 2015 Nov 1.
In this paper, facial images from various video sequences are used to obtain a heart rate reading. In this study, a video camera is used to capture the facial images of eight subjects whose heart rates vary dynamically, between 81 and 153 BPM. Principal component analysis (PCA) is used to recover the blood volume pulses (BVP) which can be used for the heart rate estimation. An important consideration for accuracy of the dynamic heart rate estimation is to determine the shortest video duration that realizes it. This video duration is chosen when the six principal components (PC) are least correlated amongst them. When this is achieved, the first PC is used to obtain the heart rate. The results obtained from the proposed method are compared to the readings obtained from the Polar heart rate monitor. Experimental results show the proposed method is able to estimate the dynamic heart rate readings using less computational requirements when compared to the existing method. The mean absolute error and the standard deviation of the absolute errors between experimental readings and actual readings are 2.18 BPM and 1.71 BPM respectively.
在本文中，来自各种视频序列的面部图像被用于获取心率读数。在这项研究中，一台摄像机被用于捕捉八名受试者的面部图像，这些受试者的心率在81至153次/分钟之间动态变化。主成分分析（PCA）被用于恢复可用于心率估计的血容量脉搏（BVP）。动态心率估计准确性的一个重要考量是确定实现该估计的最短视频时长。当六个主成分（PC）之间的相关性最小时，选择该视频时长。当达到这一条件时，使用第一个主成分来获取心率。将所提方法获得的结果与从 Polar 心率监测器获得的读数进行比较。实验结果表明，与现有方法相比，所提方法能够以较少的计算需求来估计动态心率读数。实验读数与实际读数之间的平均绝对误差和绝对误差的标准偏差分别为2.18次/分钟和1.71次/分钟。
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