Facial Remote Photoplethysmography for Continuous Heart Rate Monitoring during Prolonged Cold Liquid Bolus Administration.

Mahdi Momeni, Sophie Wuthe, Michaela Bitten Molmer, Emilie Lobner Svendsen, Mikkel Brabrand, Peter Biesenbach, Daniel Teichmann
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引用次数: 0

Abstract

This study investigates non-contact heart rate (HR) monitoring through camera-based remote PPG during intravenous fluid bolus (FB) therapy. The experiment, at Odense University Hospital, Denmark, involved 4 volunteers and over 350 minutes of filming. We implemented a MATLAB-based HR extraction tool chain. The proposed method includes a two-stage process for dynamically determining regions of interest (ROIs), incorporating deep learning for facial landmarks detection and a subsequential consideration of subjects' facial dimensions. HR estimation uses chrominance-based (CHROM) and plane-orthogonal-to-skin (POS) PPG signal extraction methods, chosen for robustness against motion artifacts. Deviating from usual advice for other methods, omitting preprocessing minimizes signal processing still yielding a low error rate. The system achieved a mean error of fewer than 2 beats per minute (bpm), underscoring iPPG's alignment with ground truth. The results exemplify the feasibility of remote PPG monitoring in critical care and emergency settings.

长时间冷液丸给药期间连续心率监测的面部远程光容积脉搏波描记术。
本研究探讨了在静脉输液(FB)治疗期间通过基于摄像机的远程PPG进行非接触式心率(HR)监测。这项实验在丹麦欧登塞大学医院进行,有4名志愿者参与,拍摄了350多分钟。我们实现了一个基于matlab的人力资源提取工具链。所提出的方法包括一个动态确定感兴趣区域(roi)的两阶段过程,结合深度学习进行面部地标检测,并随后考虑受试者的面部尺寸。HR估计使用基于色度(CHROM)和平面正交皮肤(POS) PPG信号提取方法,选择对运动伪像的鲁棒性。与通常对其他方法的建议不同,省略预处理可以最大限度地减少信号处理,但仍然产生较低的错误率。该系统的平均误差低于每分钟2次(bpm),强调了iPPG与地面真实情况的一致性。结果说明了在重症监护和急诊环境中远程监测PPG的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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