  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.
