Literature DB >> 24108484

Design and evaluation of RFID deployments in a trauma resuscitation bay.

Siddika Parlak, Shriniwas Ayyer, Ying Yu Liu, Ivan Marsic.   

Abstract

We examined configuring a radio frequency identification (RFID) equipment for the best object use detection in a trauma bay. Unlike prior work on RFID, we 1) optimized the accuracy of object use detection rather than just object detection; and 2) quantitatively assessed antenna placement while addressing issues specific to tag placement likely to occur in a trauma bay. Our design started with an analysis of the environment requirements and constraints. We designed several antenna setups with different number of components (RFID tags or antennas) and their orientations. Setups were evaluated under scenarios simulating a dynamic medical setting. We used three metrics with increasing complexity and bias: read rate, received signal strength indication distribution distance, and target application performance. Our experiments showed that antennas above the regions with high object density are most suitable for detecting object use. We explored tagging strategies for challenging objects so that sufficient readout rates are obtained for computing evaluation metrics. Among the metrics, distribution distance was correlated with target application performance, and also less biased and simpler to calculate, which made it an excellent metric for context-aware applications. We present experimental results obtained in the real trauma bay to validate our findings.

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Year:  2013        PMID: 24108484     DOI: 10.1109/JBHI.2013.2283506

Source DB:  PubMed          Journal:  IEEE J Biomed Health Inform        ISSN: 2168-2194            Impact factor:   5.772


  3 in total

1.  Deep Neural Network for RFID-Based Activity Recognition.

Authors:  Xinyu Li; Yanyi Zhang; Mengzhu Li; Ivan Marsic; JaeWon Yang; Randall S Burd
Journal:  Proc Eighth Wirel Stud Stud Stud Workshop (2016)       Date:  2016-10

2.  Object motion detection based on passive UHF RFID tags using a hidden Markov model-based classifier.

Authors:  Young Ho Lee; Ivan Marsic
Journal:  Sens Biosensing Res       Date:  2018-10-28

3.  Measuring intraoperative surgical instrument use with radio-frequency identification.

Authors:  Ian Hill; Lindsey Olivere; Joshua Helmkamp; Elliot Le; Westin Hill; John Wahlstedt; Phillip Khoury; Jared Gloria; Marc J Richard; Laura H Rosenberger; Patrick J Codd
Journal:  JAMIA Open       Date:  2022-01-19
  3 in total

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