Multimedia Tools and Applications

, Volume 78, Issue 5, pp 5427–5444 | Cite as

Development of a methodology to predict and monitor emergency situations of the elderly based on object detection

  • Sekyoung Youm
  • Changgyun Kim
  • Seunghyun Choi
  • Yong-Shin KangEmail author


Because on the increase in the number of the elderly living alone and accidents occurring to them, the demand for a monitoring system capable of supporting fast response in case of an emergency situation by monitoring their everyday life in their residential spaces has been increasing. A framework and a system are presented to monitor the emergency situations of the elderly living alone using a low-cost device and open-source software. First, human pose recognition and emergency situations according to the pose change were defined using object recognition, and a procedure capable of detecting such situations was proposed. In addition, a pose recognition model was created using the TensorFlow Object Detection application programming interface (API) of Google to implement the procedure. Using a data preprocessing process and the created model, a system capable of detecting emergency situations and sounding an alarm was implemented. To verify the proposed system, the pose recognition success rate was examined, and an experiment on emergency situation recognition was performed while the angle and distance of the camera were varied in a setup similar to the residential environment. It is expected that the proposed framework for the emergency notification system for the elderly will be utilized for the analysis of various behavior patterns, such as the sudden abnormal behavior of the elderly, people with disabilities, and children.


TensorFlow Pose recognition The elderly Emergency situation recognition Object-detection 



This work was supported by the Ministry of Land, Infrastructure and Transport in Korea.



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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Sekyoung Youm
    • 1
  • Changgyun Kim
    • 1
  • Seunghyun Choi
    • 1
  • Yong-Shin Kang
    • 2
    Email author
  1. 1.Department of Industrial and System EngineeringDongguk UniversitySeoulSouth Korea
  2. 2.Department of Systems Management EngineeringSungkyunkwan UniversitySuwonSouth Korea

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