Dipartimento di Informazione, Elettronica e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy.
Sensors (Basel). 2020 Oct 27;20(21):6102. doi: 10.3390/s20216102.
The problem of performing remote biomedical measurements using just a video stream of a subject face is called remote photoplethysmography (rPPG). The aim of this work is to propose a novel method able to perform rPPG using single-photon avalanche diode (SPAD) cameras. These are extremely accurate cameras able to detect even a single photon and are already used in many other applications. Moreover, a novel method that mixes deep learning and traditional signal analysis is proposed in order to extract and study the pulse signal. Experimental results show that this system achieves accurate results in the estimation of biomedical information such as heart rate, respiration rate, and tachogram. Lastly, thanks to the adoption of the deep learning segmentation method and dependability checks, this method could be adopted in non-ideal working conditions-for example, in the presence of partial facial occlusions.
使用主体面部的视频流进行远程生物医学测量的问题被称为远程光体积描记术（rPPG）。本工作的目的是提出一种使用单光子雪崩二极管（SPAD）相机进行 rPPG 的新方法。这些相机非常精确，能够检测到单个光子，并且已经在许多其他应用中使用。此外，还提出了一种将深度学习和传统信号分析相结合的新方法，以提取和研究脉冲信号。实验结果表明，该系统在估计心率、呼吸率和脉图等生物医学信息方面取得了精确的结果。最后，由于采用了深度学习分割方法和可靠性检查，该方法可以在非理想工作条件下采用，例如在存在部分面部遮挡的情况下。
