Detecting Out-of-Bed Activities to Prevent Pneumonia for Hospitalized Patient Using Microsoft Kinect V2

Liang Liu, Sanjay Mehrotra

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

3 Scopus citations

Abstract

This work describes a method of preventing pneumonia in the hospital room by automatically quantifying how much and how often the patient is active out-of-bed using Microsoft Kinect V2. Hospital Acquired Pneumonia (HAP) is closely associated with patient activities during patient's hospital stay. From a perspective of the healthcare staff, it is very essential to know the quantity of the patient's active time, especially when the patient is alone. The proposed system could recognize the out-of-bed activities using the features extracted from Kinect skeleton model. The observation on the detection results could provide information to healthcare staff to better understand the potential HAP formation and adjust the treatment plan in time.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 IEEE 1st International Conference on Connected Health
Subtitle of host publicationApplications, Systems and Engineering Technologies, CHASE 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages364-365
Number of pages2
ISBN (Electronic)9781509009435
DOIs
StatePublished - Aug 16 2016
Event1st IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2016 - Washington, United States
Duration: Jun 27 2016Jun 29 2016

Other

Other1st IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2016
CountryUnited States
CityWashington
Period6/27/166/29/16

Keywords

  • activities detection
  • patient monitoring

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems and Management
  • Biomedical Engineering
  • Computer Networks and Communications
  • Hardware and Architecture

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