视频中头部运动脉冲检测

Guha Balakrishnan, F. Durand, J. Guttag
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引用次数: 508

摘要

我们从视频中提取心率和心跳长度,方法是测量每次心跳时血液流入时的牛顿反应引起的细微头部运动。我们的方法跟踪头部特征,并执行主成分分析(PCA)将其轨迹分解为一组分量运动。然后,它根据时间频谱选择最符合心跳的分量。最后,我们分析了投射到该分量的运动,并识别了与心跳对应的轨迹峰值。当对18名受试者进行评估时,我们的方法报告的心率几乎与心电图设备相同。此外,我们还能够获得有关心率变异性的临床相关信息。
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Detecting Pulse from Head Motions in Video
We extract heart rate and beat lengths from videos by measuring subtle head motion caused by the Newtonian reaction to the influx of blood at each beat. Our method tracks features on the head and performs principal component analysis (PCA) to decompose their trajectories into a set of component motions. It then chooses the component that best corresponds to heartbeats based on its temporal frequency spectrum. Finally, we analyze the motion projected to this component and identify peaks of the trajectories, which correspond to heartbeats. When evaluated on 18 subjects, our approach reported heart rates nearly identical to an electrocardiogram device. Additionally we were able to capture clinically relevant information about heart rate variability.
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