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research-article

Activity recognition for emergency care using RFID

Authors:

Siddika Parlak,

Randall S. BurdAuthors Info & Claims

BodyNets '11: Proceedings of the 6th International Conference on Body Area Networks

Pages 40 - 46

Published: 07 November 2011 Publication History

Abstract

We present a system that recognizes human activities during trauma resuscitation, the fast-paced and team-based initial management of injured patients in the emergency department. Most objects used in trauma resuscitation are uniquely associated with tasks. To detect object use, we employed passive radio frequency identification (RFID) for their size and cost advantages. We designed the system setup to ensure the effectiveness of passive tags in such a complex setting, which includes various objects and significant human motion. Through our studies conducted at a Level 1 trauma center, we learned that objects used in trauma resuscitation need to be tagged differently because of their size, shape, and material composition. Based on this insight, we classified the medical items into groups based on usage and other characteristics. Objects in different groups are tagged differently and their data is processed differently. We applied machine-learning algorithms to identify object-state changes and process the RFID data using algorithms specific to object groups. Our results show that RFID has significant potential for automatic detection of object usage in complex and fast-paced settings.

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Cited By

Ding FZhang QZhao RWang DMüller PMostefaoui A(2018)TTBAProceedings of the 14th ACM International Symposium on QoS and Security for Wireless and Mobile Networks10.1145/3267129.3267133(7-14)Online publication date: 25-Oct-2018
https://dl.acm.org/doi/10.1145/3267129.3267133
Mathisen ASørensen SStisen ABlunck HGrønbæk KGu TKotagiri RLiu H(2017)A Study on the Impact of Indoor Positioning Performance on Activity Recognition ApplicationsProceedings of the 14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services10.1145/3144457.3144501(58-67)Online publication date: 7-Nov-2017
https://dl.acm.org/doi/10.1145/3144457.3144501
Yao LSheng QNgu ALi XBenattalah B(2017)Unveiling Correlations via Mining Human-Thing Interactions in the Web of ThingsACM Transactions on Intelligent Systems and Technology10.1145/30359678:5(1-25)Online publication date: 30-Jun-2017
https://dl.acm.org/doi/10.1145/3035967
Show More Cited By

Index Terms

Activity recognition for emergency care using RFID
1. Applied computing
  1. Life and medical sciences
    1. Consumer health
    2. Health informatics
2. Information systems
  1. Information systems applications

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Information & Contributors

Information

Published In

cover image ACM Other conferences

BodyNets '11: Proceedings of the 6th International Conference on Body Area Networks

November 2011

135 pages

ISBN:9781936968299

General Chair:
Yunhao Liu
Tsinghua University, China
,
Program Chairs:
Roozbeh Jafari
University of Texas at Dallas
,
Chenyang Lu
Washington University

Sponsors

ICST

In-Cooperation

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering)

Brussels, Belgium

Publication History

Published: 07 November 2011

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BodyNets '11

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BodyNets '11: The 6th ICST Conference on Body Area Networks

November 7 - 8, 2011

Beijing, China

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Cited By

Ding FZhang QZhao RWang DMüller PMostefaoui A(2018)TTBAProceedings of the 14th ACM International Symposium on QoS and Security for Wireless and Mobile Networks10.1145/3267129.3267133(7-14)Online publication date: 25-Oct-2018
https://dl.acm.org/doi/10.1145/3267129.3267133
Mathisen ASørensen SStisen ABlunck HGrønbæk KGu TKotagiri RLiu H(2017)A Study on the Impact of Indoor Positioning Performance on Activity Recognition ApplicationsProceedings of the 14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services10.1145/3144457.3144501(58-67)Online publication date: 7-Nov-2017
https://dl.acm.org/doi/10.1145/3144457.3144501
Yao LSheng QNgu ALi XBenattalah B(2017)Unveiling Correlations via Mining Human-Thing Interactions in the Web of ThingsACM Transactions on Intelligent Systems and Technology10.1145/30359678:5(1-25)Online publication date: 30-Jun-2017
https://dl.acm.org/doi/10.1145/3035967
Yao LSheng QNgu AGao BLi JWang XGarofalakis MSoboroff ISuel TWang M(2014)Keeping You in the LoopProceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management10.1145/2661829.2661838(2027-2029)Online publication date: 3-Nov-2014
https://dl.acm.org/doi/10.1145/2661829.2661838
Parlak SSarcevic AMarsic IBurd R(2012)Introducing RFID technology in dynamic and time-critical medical settingsJournal of Biomedical Informatics10.1016/j.jbi.2012.04.00345:5(958-974)Online publication date: 1-Oct-2012
https://dl.acm.org/doi/10.1016/j.jbi.2012.04.003

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