TY - JOUR
T1 - A mobile robot for fall detection for elderly-care
AU - Sumiya, Takuma
AU - Matsubara, Yutaka
AU - Nakano, Miyuki
AU - Sugaya, Midori
N1 - Publisher Copyright:
© 2015 The Authors. Published by Elsevier B.V.
PY - 2015
Y1 - 2015
N2 - 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.
AB - 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.
KW - Human detection
KW - Mobile robot
KW - Welfare
UR - http://www.scopus.com/inward/record.url?scp=84941086005&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84941086005&partnerID=8YFLogxK
U2 - 10.1016/j.procs.2015.08.250
DO - 10.1016/j.procs.2015.08.250
M3 - Conference article
AN - SCOPUS:84941086005
SN - 1877-0509
VL - 60
SP - 870
EP - 880
JO - Procedia Computer Science
JF - Procedia Computer Science
IS - 1
T2 - 19th International Conference on Knowledge Based and Intelligent Information and Engineering Systems, KES 2015
Y2 - 7 September 2015 through 9 September 2015
ER -