A mobile robot for fall detection for elderly-care

Takuma Sumiya, Yutaka Matsubara, Miyuki Nakano, Midori Sugaya

Research output: Contribution to journalConference articlepeer-review

26 Citations (Scopus)


In 2015, the population of people over the age of 65 is 25.0% in Japan. This means that Japan has already become a super-aging society. In such society, the number of elderly people living alone has been also increased. For such people, a fall accident is serious because it can lead to serious injury or death. Researches and services to monitor behaviours of such people have been proposed. For example, by monitoring the status of use of home appliances, something unusual happened to them can be predicted. However, such systems cannot recognize the detailed behaviours like fall. Surveillance cameras have been introduced only outside the house because of the privacy issues. In this paper, we propose a mobile robot to detect human fall and report it to their observers. The mobile robot consists of a household mobile robot (Yujin Robot's Kobuki), a sensor (Microsoft's Kinect), and a computer (PC) to detect a human and control the robot. For simplicity of the robot and accurate fall detection, the sensor is installed on the robot to follow the target harmoniously. Thus, the sensor can move around with the robot to minimize blind area. The results of our experiments show that improvement of up to 80% in fall detection rate compared to a conventional monitoring technique using position-fixed sensors. Finally, we discuss the capabilities and future works of the robot.

Original languageEnglish
Pages (from-to)870-880
Number of pages11
JournalProcedia Computer Science
Issue number1
Publication statusPublished - 2015
Event19th International Conference on Knowledge Based and Intelligent Information and Engineering Systems, KES 2015 - , Singapore
Duration: 2015 Sept 72015 Sept 9


  • Human detection
  • Mobile robot
  • Welfare

ASJC Scopus subject areas

  • General Computer Science


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