A study on a fall detection monitoring system for falling elderly using open source hardware

Seunghyun Choi, Sekyoung Youm

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Due to the rapid increase in the elderly population and single-person households, it is absolutely necessary to observe the indoor activities of marginalized people, such as the elderly or the disabled, to detect abnormal conditions. At this time, contact sensors are have limited applicability due to their continuous wear, so there is a need to develop technology to collect daily life activities of the elderly. In this study, we tried to track the elderly living alone using images obtained from an open source camera. The system captures images by linking a low-cost camera module to open source hardware, and an algorithm is implemented to detect falls. This system can be used to reduce the cost of social care by improving the cost of care in the aging population, and this will contribute to promoting and developing management prescription guidelines through risk detection.

Original languageEnglish
Pages (from-to)28423-28434
Number of pages12
JournalMultimedia Tools and Applications
Volume78
Issue number20
DOIs
StatePublished - 1 Oct 2019

Keywords

  • Elder
  • Fall detection
  • Monitoring
  • Open source hardware

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