Process monitoring in the intensive care unit: Assessing patient mobility through activity analysis with a non-invasive mobility sensor

Austin Reiter, Andy Ma, Nishi Rawat, Christine Shrock, Suchi Saria

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Throughout a patient’s stay in the Intensive Care Unit (ICU),accurate measurement of patient mobility,as part of routine care,is helpful in understanding the harmful effects of bedrest [1]. However,mobility is typically measured through observation by a trained and dedicated observer,which is extremely limiting. In this work,we present a video-based automated mobility measurement system called NIMS: Non-Invasive Mobility Sensor. Our main contributions are: (1) a novel multi-person tracking methodology designed for complex environments with occlusion and pose variations,and (2) an application of human-activity attributes in a clinical setting. We demonstrate NIMS on data collected from an active patient room in an adult ICU and show a high inter-rater reliability using a weighted Kappa statistic of 0.86 for automatic prediction of the highest level of patient mobility as compared to clinical experts.

Original languageEnglish (US)
Title of host publicationMedical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings
PublisherSpringer Verlag
Pages482-490
Number of pages9
Volume9900 LNCS
ISBN (Print)9783319467191
DOIs
StatePublished - 2016
Event1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016 - Athens, Greece
Duration: Oct 21 2016Oct 21 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9900 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016
CountryGreece
CityAthens
Period10/21/1610/21/16

Keywords

  • Activity recognition
  • Patient safety
  • Tracking

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Reiter, A., Ma, A., Rawat, N., Shrock, C., & Saria, S. (2016). Process monitoring in the intensive care unit: Assessing patient mobility through activity analysis with a non-invasive mobility sensor. In Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings (Vol. 9900 LNCS, pp. 482-490). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9900 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-46720-7_56