The need for remote tools for healthcare monitoring has never been more apparent. Camera measurement of vital signs leverages imaging devices to compute physiological changes by analyzing images of the human body. Building on advances in optics, machine learning, computer vision and medicine these techniques have progressed significantly since the invention of digital cameras. This paper presents a comprehensive survey of camera measurement of physiological vital signs, describing they vital signs that can be measured and the computational techniques for doing so. I cover both clinical and non-clinical applications and the challenges that need to be overcome for these applications to advance from proofs-of-concept. Finally, I describe the current resources (datasets and code) available to the research community and provide a comprehensive webpage (https://cameravitals.github.io/) with links to these resource and a categorized list of all the papers referenced in this article.
翻译：对远程保健监测工具的需要从未如此明显。对生命迹象的摄影测量利用成像装置分析人体图像来计算生理变化。这些技术在光学、机器学习、计算机视觉和医学方面的进步的基础上,自数字照相机发明以来取得了显著进展。本文对摄影机测量生理生命迹象的情况进行了全面调查,描述了这些迹象可以测量的重要迹象以及这样做的计算技术。我既包括临床和非临床应用,也包括这些应用需要克服的挑战,以便从概念证据中推进这些应用。最后,我描述了研究界现有的资源(数据集和代码),并提供与这些资源链接的综合网页(https://cameravitals.github.io/),并列出了本文章引用的所有文件的分类清单。
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