A Pilot Study of Deep Learning Models for Camera based Hand Hygiene Monitoring in ICU

Weijun Huang1; Jia Huang2; Guowei Wang2; Hongzhou Lu2; Min He3; Wenjin Wang1

10.1109/EMBC40787.2023.10341146

2023

45th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

2375-7477

1558-4615

979-8-3503-2448-8

2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

1-5

24-27 July 2023

Sydney, Australia

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

Hand hygiene is key to preventing cross-infections in the Intensive Care Unit (ICU). Monitoring of hand washing activities can effectively increase the compliance of clinicians to hand hygiene. In this paper, we explored the feasibility of recognizing clinicians' hand-washing activities using a clinical dataset recorded in ICU using CCTV cameras. We benchmarked three types of hand hygiene detection methods on the dataset with the aim of identifying the 7-step hand washing procedure defined by WHO. Experimental results show that our approach achieves 97% average accuracy for personalized and 67% for generalized modeling. Preliminary results indicate that hand hygiene recognition is subject-dependent, and thus cross-subject modeling or subject-adaptive learning should be used to enhance generalization. The feasibility and challenges of CCTV-camera-based hand hygiene recognition are discussed. The results may contribute to design a hand hygiene scoring and alert system as part of the IoT system in hospitals. The hospital data and code are available at https://github.com/SunnySideUp11/ICU-MH-20

Hand hygiene CCTV cameras benchmark deep learning

第一

英语

EI ; CPCI-S

National Key R&D Program of China[2022YFC2407800]

Computer Science ; Engineering

Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications ; Engineering, Biomedical

WOS:001133788305028

20240215362235

Deep learning ; Learning systems ; Video cameras ; Washing

Ergonomics and Human Factors Engineering:461.4 ; Hospitals, Equipment and Supplies:462.2 ; Television Systems and Equipment:716.4 ; Photographic Equipment:742.2

IEEE

1.Department of Biomedical Engineering, Southern University of Science and Technology, China
2.Intensive Care Unit, The Third People’s Hospital of Shenzhen, China
3.Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, China

Weijun Huang,Jia Huang,Guowei Wang,et al. A Pilot Study of Deep Learning Models for Camera based Hand Hygiene Monitoring in ICU[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2023:1-5.