A Multi-Channel Ratio-of-Ratios Method for Noncontact Hand Video Based SpO$_2$ Monitoring Using Smartphone Cameras
A Multi-Channel Ratio-of-Ratios Method for Noncontact Hand Video Based SpO$_2$ Monitoring Using Smartphone Cameras
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DOI：
10.1109/jstsp.2022.3152352
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发表时间：
2021-07
影响因子：
7.5
通讯作者：
Xin Tian;Chau-Wai Wong;S. Ranadive;Min Wu
中科院分区：
文献类型：
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作者：
Xin Tian;Chau-Wai Wong;S. Ranadive;Min Wu
血氧饱和度（SpO$_2$）是肺和呼吸功能的重要指标。 COVID-19 的临床研究结果表明，许多患者在病情恶化前不久就出现了危险的低血氧水平。因此，建议，特别是对于弱势群体，定期监测血氧水平以进行预防。最近的工作研究了如何使用无处不在的智能手机摄像头来推断 SpO$_2$。这些作品大多数都是基于接触的，要求用户用手指遮住手机的摄像头及其附近的光源，以捕获从被照亮的组织重新发射的光。基于接触的方法可能会导致皮肤刺激和卫生问题，尤其是在大流行期间。在本文中，我们提出了一种使用智能手机获取的手部视频进行 SpO$_2$ 监测的非接触式方法。考虑到智能手机摄像头的红色 (R)、绿色 (G) 和蓝色 (B) 颜色通道的光学宽带特性，我们利用 RGB 传感的所有三个通道来提取 SpO$_2$ 信息，超越仅使用两个波长的传统比率 (RoR) 方法。为了进一步促进准确的 SpO$_2$ 预测，我们根据准确估计的心率设计了自适应窄带通滤波器，以获得每个颜色通道与心脏最相关的 AC 分量。实验结果表明，当以脉搏血氧计作为参考时，我们提出的血氧估计方法可以达到平均绝对误差1.26%，比传统的RoR方法高25%。
Blood oxygen saturation (SpO$_2$) is an important indicator forpulmonary and respiratory functionalities. Clinical findings on COVID-19 show that many patients had dangerously low blood oxygen levels not long before conditions worsened. It is therefore recommended, especially for the vulnerable population, to regularly monitor the blood oxygen level for precaution. Recent works have investigated how ubiquitous smartphone cameras can be used to infer SpO$_2$. Most of these works are contact-based, requiring users to cover a phone’s camera and its nearby light source with a finger to capture reemitted light from the illuminated tissue. Contact-based methods may lead to skin irritation and sanitary concerns, especially during a pandemic. In this paper, we propose a noncontact method for SpO$_2$ monitoring using hand videos acquired by smartphones. Considering the optical broadband nature of the red (R), green (G), and blue (B) color channels of the smartphone cameras, we exploit all three channels of RGB sensing to distill the SpO$_2$ information beyond the traditional ratio-of-ratios (RoR) method that uses only two wavelengths. To further facilitate an accurate SpO$_2$ prediction, we design adaptive narrow bandpass filters based on accurately estimated heart rate to obtain the most cardiac-related AC component for each color channel. Experimental results show that our proposed blood oxygen estimation method can reach a mean absolute error of 1.26% when a pulse oximeter is used as a reference, outperforming the traditional RoR method by 25%.