Year: 2022
Type: article
Abstract: 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 32 000 frames from the videos of patients recorded in an intensive care unit to clinical agitation scores recorded by clinical workers.
Source: IEEE Sensors Letters
Authors: Thanh Nguyen-Duc, Andrew Tay, David Chen, John Tan Nguyen, Jessica Lyall, Maria De Freitas, Peter Y. Chan
Institutions: Monash University, Eastern Health
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4285217543