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

doi:10.1007/978-3-319-46720-7_56

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 proceeding › Conference contribution

3 Scopus citations

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 language	English (US)
Title of host publication	Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings
Editors	Sebastian Ourselin, Leo Joskowicz, Mert R. Sabuncu, William Wells, Gozde Unal
Publisher	Springer Verlag
Pages	482-490
Number of pages	9
ISBN (Print)	9783319467191
DOIs	https://doi.org/10.1007/978-3-319-46720-7_56
State	Published - 2016
Event	1st 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 2016 → Oct 21 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9900 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	1st 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
Country/Territory	Greece
City	Athens
Period	10/21/16 → 10/21/16

Keywords

Activity recognition
Patient safety
Tracking

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-46720-7_56

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 S. Ourselin, L. Joskowicz, M. R. Sabuncu, W. Wells, & G. Unal (Eds.), Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings (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

Process monitoring in the intensive care unit: Assessing patient mobility through activity analysis with a non-invasive mobility sensor. / Reiter, Austin; Ma, Andy; Rawat, Nishi et al.
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. ed. / Sebastian Ourselin; Leo Joskowicz; Mert R. Sabuncu; William Wells; Gozde Unal. Springer Verlag, 2016. p. 482-490 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9900 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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 S Ourselin, L Joskowicz, MR Sabuncu, W Wells & G Unal (eds), Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9900 LNCS, Springer Verlag, pp. 482-490, 1st 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, 10/21/16. https://doi.org/10.1007/978-3-319-46720-7_56

Reiter A, Ma A, Rawat N, Shrock C, Saria S. Process monitoring in the intensive care unit: Assessing patient mobility through activity analysis with a non-invasive mobility sensor. In Ourselin S, Joskowicz L, Sabuncu MR, Wells W, Unal G, editors, Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. Springer Verlag. 2016. p. 482-490. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-46720-7_56

Reiter, Austin ; Ma, Andy ; Rawat, Nishi et al. / Process monitoring in the intensive care unit : Assessing patient mobility through activity analysis with a non-invasive mobility sensor. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. editor / Sebastian Ourselin ; Leo Joskowicz ; Mert R. Sabuncu ; William Wells ; Gozde Unal. Springer Verlag, 2016. pp. 482-490 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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

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