Contactless monitoring using thermal imaging has become increasingly proposed to monitor patient deterioration in hospital, most recently to detect fevers and infections during the COVID-19 pandemic. In this letter, we propose a novel method to estimate patient motion and observe clinical workload using a similar technical setup but combined with open source object detection algorithms (YOLOv4) and optical flow. Patient motion estimation was used to approximate patient agitation and sedation, while worker motion was used as a surrogate for caregiver workload. Performance was illustrated by comparing over 32000 frames from videos of patients recorded in an Intensive Care Unit, to clinical agitation scores recorded by clinical workers.

翻译：使用热成像的无接触监测越来越多地被提议监测医院病人恶化情况,最近一次是检测COVID-19大流行期间的发烧和感染情况,在本信中,我们提议采用一种新的方法,利用类似的技术装置,与开源物体探测算法(YOLOv4)和光学流相结合,估计病人运动估计接近病人的焦虑和镇静,而工人运动则用作护理员工作量的代孕。