Patient Associated Motion Detection with Optical Flow Using Microsoft Kinect V2

Liang Liu, Sanjay Mehrotra

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

2 Scopus citations

Abstract

This work describes our recent work of detecting the patient associated motions in a hospital room. After we had installed the designed Kinect V2 sensor-based health system in the hospital, we began to face big data challenges. The acquired data is big in both size and content. In this paper, we will propose a method to filter the big data using optical flow methods. As a result, we can discard the unnecessary data and quickly target on the data including valuable motion information about the patient. The proposed methodology facilitates the follow-up activity detection and serves for evaluating the amount of the movement the patient generates to allow the caregiver to improve the treatment plan.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE 2nd International Conference on Connected Health
Subtitle of host publicationApplications, Systems and Engineering Technologies, CHASE 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages274-275
Number of pages2
ISBN (Electronic)9781509047215
DOIs
StatePublished - Aug 14 2017
Event2nd IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2017 - Philadelphia, United States
Duration: Jul 17 2017Jul 19 2017

Other

Other2nd IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2017
CountryUnited States
CityPhiladelphia
Period7/17/177/19/17

Keywords

  • motion detection
  • optical flow
  • Patient monitoring

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Health(social science)
  • Communication
  • Computer Science Applications
  • Software
  • Biomedical Engineering
  • Health Informatics

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