Li Fen, Zhao Yuejin, Kong Lingqin, Dong Liquan, Liu Ming, Hui Mei, Liu Xiaohua
Beijing Key Laboratory for Precision Optoelectronic Measurement Instrument and Technology, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China.
Rev Sci Instrum. 2020 May 1;91(5):054105. doi: 10.1063/1.5128806.
Recent studies have shown that head movements associated with cardiac activity contain a heart rate (HR) signal. In most previous studies, subjects were required to remain stationary in a specific environment during HR measurements, and measurement accuracy depended on the choice of target in the scene, i.e., the specified region of the face. In this paper, we proposed a robust HR measurement method based on ballistocardiogram (BCG) technology. This method requires only a camera and does not require that users establish a complex measurement environment. In addition, a bidirectional optical flow algorithm is designed to select and track valid feature points in the video captured by using the camera. Experiments with 11 subjects show that the HR values measured using the proposed method differ slightly from the reference values, and the average error is only 1.09%. Overall, this method can improve the accuracy of BCG without limitations related to skin tone, illumination, the state of the subject, or the test location.
最近的研究表明,与心脏活动相关的头部运动包含心率(HR)信号。在大多数先前的研究中,受试者在心率测量期间需要在特定环境中保持静止,并且测量精度取决于场景中目标的选择,即面部的指定区域。在本文中,我们提出了一种基于心冲击图(BCG)技术的稳健心率测量方法。该方法仅需要一台相机,并且不需要用户建立复杂的测量环境。此外,设计了一种双向光流算法,用于选择和跟踪使用相机捕获的视频中的有效特征点。对11名受试者进行的实验表明,使用所提出的方法测量的心率值与参考值略有不同,平均误差仅为1.09%。总体而言,该方法可以提高BCG的准确性,而不受肤色、光照、受试者状态或测试位置的限制。