Logo image
Activity Recognition for Medical Teamwork Based on Passive RFID
Conference proceeding   Open access

Activity Recognition for Medical Teamwork Based on Passive RFID

Xinyu Li, Dongyang Yao, Xuechao Pan, Jonathan Johannaman, JaeWon Yang, Rachel Webman, Aleksandra Sarcevic, Ivan Marsic and Randall S Burd
2016 IEEE International Conference on RFID (RFID), v 2016
May 2016
PMID: 30370332
url
https://europepmc.org/articles/pmc6200354View
Accepted (AM)Open Access (License Unspecified) Open

Abstract

passive RFID tagging strategies object-use detection activity recognition Machine Learning
We describe a novel and practical activity recognition system for dynamic and complex medical settings using only passive RFID technology. Our activity recognition approach is based on the use of objects that are specific for a given activity. The object-use status is detected from RFID data and the activities are predicted from the statuses of use of different objects. We tagged 10 objects in a trauma room of an emergency department and recorded RFID data for 10 actual trauma resuscitations. More than 20,000 seconds of data were collected and used for analysis. The system achieved a 96% overall accuracy with a 0.74F-score for detecting use of 10 common resuscitation objects and 95% accuracy with a 0.30 F Score for activity recognition of 10 medical activities.

Metrics

16 Record Views
23 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Collaboration types
Domestic collaboration
Web of Science research areas
Engineering, Electrical & Electronic
Logo image