Detection of patient's bed statuses in 3D using a Microsoft Kinect

Yun Li*, Lyle Berkowitz, Gary A Noskin, Sanjay Mehrotra

*Corresponding author for this work

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

13 Citations (Scopus)

Abstract

Patients spend the vast majority of their hospital stay in an unmonitored bed where various mobility factors can impact patient safety and quality. Specifically, bed positioning and a patient's related mobility in that bed can have a profound impact on risks such as pneumonias, blood clots, bed ulcers and falls. This issue has been exacerbated as the nurse-per-bed (NPB) ratio has decreased in recent years. To help assess these risks, it is critical to monitor a hospital bed's positional status (BPS). Two bed positional statuses, bed height (BH) and bed chair angle (BCA), are of critical interests for bed monitoring. In this paper, we develop a bed positional status detection system using a single Microsoft Kinect. Experimental results show that we are able to achieve 94.5% and 93.0% overall accuracy of the estimated BCA and BH in a simulated patient's room environment.

Original languageEnglish (US)
Title of host publication2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5900-5903
Number of pages4
ISBN (Electronic)9781424479290
DOIs
StatePublished - Nov 2 2014
Event2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 - Chicago, United States
Duration: Aug 26 2014Aug 30 2014

Publication series

Name2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014

Other

Other2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
CountryUnited States
CityChicago
Period8/26/148/30/14

Fingerprint

Hospital beds
Patient Positioning
Patients' Rooms
Patient Safety
Ulcer
Length of Stay
Pneumonia
Thrombosis
Nurses
Blood
Monitoring

ASJC Scopus subject areas

  • Health Informatics
  • Computer Science Applications
  • Biomedical Engineering
  • Medicine(all)

Cite this

Li, Y., Berkowitz, L., Noskin, G. A., & Mehrotra, S. (2014). Detection of patient's bed statuses in 3D using a Microsoft Kinect. In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 (pp. 5900-5903). [6944971] (2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2014.6944971
Li, Yun ; Berkowitz, Lyle ; Noskin, Gary A ; Mehrotra, Sanjay. / Detection of patient's bed statuses in 3D using a Microsoft Kinect. 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 5900-5903 (2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014).
@inproceedings{7788e2e436fa4a09b547d8dcab6d7570,
title = "Detection of patient's bed statuses in 3D using a Microsoft Kinect",
abstract = "Patients spend the vast majority of their hospital stay in an unmonitored bed where various mobility factors can impact patient safety and quality. Specifically, bed positioning and a patient's related mobility in that bed can have a profound impact on risks such as pneumonias, blood clots, bed ulcers and falls. This issue has been exacerbated as the nurse-per-bed (NPB) ratio has decreased in recent years. To help assess these risks, it is critical to monitor a hospital bed's positional status (BPS). Two bed positional statuses, bed height (BH) and bed chair angle (BCA), are of critical interests for bed monitoring. In this paper, we develop a bed positional status detection system using a single Microsoft Kinect. Experimental results show that we are able to achieve 94.5{\%} and 93.0{\%} overall accuracy of the estimated BCA and BH in a simulated patient's room environment.",
author = "Yun Li and Lyle Berkowitz and Noskin, {Gary A} and Sanjay Mehrotra",
year = "2014",
month = "11",
day = "2",
doi = "10.1109/EMBC.2014.6944971",
language = "English (US)",
series = "2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "5900--5903",
booktitle = "2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014",
address = "United States",

}

Li, Y, Berkowitz, L, Noskin, GA & Mehrotra, S 2014, Detection of patient's bed statuses in 3D using a Microsoft Kinect. in 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014., 6944971, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014, Institute of Electrical and Electronics Engineers Inc., pp. 5900-5903, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014, Chicago, United States, 8/26/14. https://doi.org/10.1109/EMBC.2014.6944971

Detection of patient's bed statuses in 3D using a Microsoft Kinect. / Li, Yun; Berkowitz, Lyle; Noskin, Gary A; Mehrotra, Sanjay.

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 5900-5903 6944971 (2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014).

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

TY - GEN

T1 - Detection of patient's bed statuses in 3D using a Microsoft Kinect

AU - Li, Yun

AU - Berkowitz, Lyle

AU - Noskin, Gary A

AU - Mehrotra, Sanjay

PY - 2014/11/2

Y1 - 2014/11/2

N2 - Patients spend the vast majority of their hospital stay in an unmonitored bed where various mobility factors can impact patient safety and quality. Specifically, bed positioning and a patient's related mobility in that bed can have a profound impact on risks such as pneumonias, blood clots, bed ulcers and falls. This issue has been exacerbated as the nurse-per-bed (NPB) ratio has decreased in recent years. To help assess these risks, it is critical to monitor a hospital bed's positional status (BPS). Two bed positional statuses, bed height (BH) and bed chair angle (BCA), are of critical interests for bed monitoring. In this paper, we develop a bed positional status detection system using a single Microsoft Kinect. Experimental results show that we are able to achieve 94.5% and 93.0% overall accuracy of the estimated BCA and BH in a simulated patient's room environment.

AB - Patients spend the vast majority of their hospital stay in an unmonitored bed where various mobility factors can impact patient safety and quality. Specifically, bed positioning and a patient's related mobility in that bed can have a profound impact on risks such as pneumonias, blood clots, bed ulcers and falls. This issue has been exacerbated as the nurse-per-bed (NPB) ratio has decreased in recent years. To help assess these risks, it is critical to monitor a hospital bed's positional status (BPS). Two bed positional statuses, bed height (BH) and bed chair angle (BCA), are of critical interests for bed monitoring. In this paper, we develop a bed positional status detection system using a single Microsoft Kinect. Experimental results show that we are able to achieve 94.5% and 93.0% overall accuracy of the estimated BCA and BH in a simulated patient's room environment.

UR - http://www.scopus.com/inward/record.url?scp=84929458528&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84929458528&partnerID=8YFLogxK

U2 - 10.1109/EMBC.2014.6944971

DO - 10.1109/EMBC.2014.6944971

M3 - Conference contribution

T3 - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014

SP - 5900

EP - 5903

BT - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Li Y, Berkowitz L, Noskin GA, Mehrotra S. Detection of patient's bed statuses in 3D using a Microsoft Kinect. In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 5900-5903. 6944971. (2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014). https://doi.org/10.1109/EMBC.2014.6944971