DistancePPG: Robust non-contact vital signs monitoring using a camera
DistancePPG: Robust non-contact vital signs monitoring using a camera
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DOI：
10.1364/boe.6.001565
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发表时间：
2015-05-01
影响因子：
3.4
通讯作者：
Sabharwal, Ashutosh
中科院分区：
文献类型：
--
作者：
Kumar, Mayank;Veeraraghavan, Ashok;Sabharwal, Ashutosh
目前使用接触式探头测量脉搏率和呼吸率等生命体征。但是，用于测量生命体征的非接触方法在医院环境（例如，G.在NICU）和无处不在的原位健康跟踪（e. G.在具有网络摄像头的移动的电话和计算机上）。最近，基于相机的非接触式生命体征监测已被证明是可行的。然而，基于相机的生命体征监测对于具有较暗肤色的人、在低光照条件下和/或在个人在相机前移动期间是具有挑战性的。在本文中，我们提出了distancepPG，一个新的基于摄像头的生命体征估计算法，解决了这些挑战。DistancePPG提出了一种新的方法，使用加权平均值将来自面部不同跟踪区域的肤色变化信号组合起来，其中权重取决于该区域中的血液灌注和入射光强度，以提高基于相机的估计的信噪比（SNR）。我们的主要贡献之一是一个新的自动方法，用于确定的权重仅基于视频记录的主题。使用distancepPG估计的基于相机的PPG的SNR的增益转化为生命体征估计中的误差的减少，并且因此将基于相机的生命体征监测的范围扩展到潜在的具有挑战性的场景。此外，还将发布一个数据集，包括在不同光照条件下和各种运动场景下，来自不同肤色的人的耳垂的基于面部和脉搏血氧计的地面实况记录的同步视频记录。(C)2015美国光学学会
Vital signs such as pulse rate and breathing rate are currently measured using contact probes. But, non-contact methods for measuring vital signs are desirable both in hospital settings (e. g. in NICU) and for ubiquitous in-situ health tracking (e. g. on mobile phone and computers with webcams). Recently, camera-based non-contact vital sign monitoring have been shown to be feasible. However, camera-based vital sign monitoring is challenging for people with darker skin tone, under low lighting conditions, and/or during movement of an individual in front of the camera. In this paper, we propose distancePPG, a new camera-based vital sign estimation algorithm which addresses these challenges. DistancePPG proposes a new method of combining skin-color change signals from different tracked regions of the face using a weighted average, where the weights depend on the blood perfusion and incident light intensity in the region, to improve the signal-to-noise ratio (SNR) of camera-based estimate. One of our key contributions is a new automatic method for determining the weights based only on the video recording of the subject. The gains in SNR of camera-based PPG estimated using distancePPG translate into reduction of the error in vital sign estimation, and thus expand the scope of camera-based vital sign monitoring to potentially challenging scenarios. Further, a dataset will be released, comprising of synchronized video recordings of face and pulse oximeter based ground truth recordings from the earlobe for people with different skin tones, under different lighting conditions and for various motion scenarios. (C) 2015 Optical Society of America