title: Development of robust behaviour recognition for an at-home biomonitoring robot with assistance of subject localization and enhanced visual tracking.
abstract: Our research is focused on the development of an at-home health care biomonitoring mobile robot for the people in demand. Main task of the robot is to detect and track a designated subject while recognizing his/her activity for analysis and to provide warning in an emergency. In order to push forward the system towards its real application, in this study, we tested the robustness of the robot system with several major environment changes, control parameter changes, and subject variation. First, an improved color tracker was analyzed to find out the limitations and constraints of the robot visual tracking considering the suitable illumination values and tracking distance intervals. Then, regarding subject safety and continuous robot based subject tracking, various control parameters were tested on different layouts in a room. Finally, the main objective of the system is to find out walking activities for different patterns for further analysis. Therefore, we proposed a fast, simple, and person specific new activity recognition model by making full use of localization information, which is robust to partial occlusion. The proposed activity recognition algorithm was tested on different walking patterns with different subjects, and the results showed high recognition accuracy.
authors.affiliation: Graduate School of Engineering, Chiba University, Chiba 263-8522, Japan.
authors.forename: Nevrez
authors.initials: N
authors.lastname: Imamoglu
authors.affiliation: Research Center for Frontier Medical Engineering, Chiba University, Chiba 263-8522, Japan ; Department of Electronic Technology, University of Seville, 41012 Seville, Spain.
authors.forename: Enrique
authors.initials: E
authors.lastname: Dorronzoro
authors.affiliation: Institute of Robotics and Intelligent Information Processing, Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China.
authors.forename: Zhixuan
authors.initials: Z
authors.lastname: Wei
authors.affiliation: Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China.
authors.forename: Huangjun
authors.initials: H
authors.lastname: Shi
authors.affiliation: Graduate School of Engineering, Chiba University, Chiba 263-8522, Japan.
authors.forename: Masashi
authors.identifier: 0000-0001-7948-0606
authors.initials: M
authors.lastname: Sekine
authors.affiliation: Spanish National Research Council, Bioengineering Group, 28500 Madrid, Spain.
authors.forename: José
authors.initials: J
authors.lastname: González
authors.affiliation: Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China.
authors.forename: Dongyun
authors.initials: D
authors.lastname: Gu
authors.affiliation: Institute of Robotics and Intelligent Information Processing, Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China.
authors.forename: Weidong
authors.identifier: 0000-0001-8757-0679
authors.initials: W
authors.lastname: Chen
authors.affiliation: Research Center for Frontier Medical Engineering, Chiba University, Chiba 263-8522, Japan.
authors.forename: Wenwei
authors.initials: W
authors.lastname: Yu
mesh_terms: D004784:Environmental Monitoring; D006801:Humans; D007089:Image Enhancement; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D012371:Robotics / Q000295:instrumentation* / Q000379:methods