Development of a Breathing Detection Robot for a Monitoring System

This paper reports the development of a breathing detection method using a mobile robot for a monitoring system. We propose an autonomous monitoring framework based on the combined use of a surveillance sensor and a mobile robot. The system estimates a person's pose using the surveillance sensor. When the person falls down, the mobile robot approaches the person and checks his vital condition. In this paper, we propose a new breathing detection method. The mobile robot detects breathing based on the movement of the person's chest obtained from the depth images of a Kinect sensor. We made a prototype of the monitoring robot, and confirmed that a series of operations were performed automatically.

[1]  Horst-Michael Groß,et al.  Fallen Person Detection for Mobile Robots Using 3D Depth Data , 2013, 2013 IEEE International Conference on Systems, Man, and Cybernetics.

[2]  Franck Multon,et al.  Fall Detection With Multiple Cameras: An Occlusion-Resistant Method Based on 3-D Silhouette Vertical Distribution , 2011, IEEE Transactions on Information Technology in Biomedicine.

[3]  Dimitrios Makris,et al.  Fall detection system using Kinect’s infrared sensor , 2014, Journal of Real-Time Image Processing.

[4]  Simon Fielden,et al.  Fall detectors: a review of the literature , 2012 .

[5]  Max Mignotte,et al.  Fall Detection from Depth Map Video Sequences , 2011, ICOST.

[6]  Jun Miura,et al.  Autonomous monitoring framework with fallen person pose estimation and vital sign detection , 2014, 2014 6th International Conference on Information Technology and Electrical Engineering (ICITEE).

[7]  Tong Zhang,et al.  Fall Detection by Wearable Sensor and One-Class SVM Algorithm , 2006 .