¹School of Engineering and Physics, The University of the South Pacific, Suva, Fiji.
²Department of Industrial and Production Engineering Jessore University of Science and Technology, Jessore-7408, Bangladesh.
³School of Mechanical and Manufacturing Engineering Dublin City University, Dublin 9, Ireland.

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Abstract—In this paper an intelligent system for remote patient physical condition monitoring service module for an Intelligent Robot Swarm for Attendance, Recognition, Cleaning and Delivery (iWARD) [1] is reported. The system algorithm and module software is implemented in C/C++, and the Orca robotics [2] components use the OpenCV [3] image analysis and processing library. The system is successfully tested on Linux (Ubuntu) platform as well as on a web server. The patient condition monitoring system can remotely measure the following body conditions: body temperature (BTemp), heart rate (HR), electrocardiogram (ECG), respiration rate (RR), body acceleration (BA) using sensors attached to the patient’s body. The system also includes an RGB video camera and a 3D laser sensor, which monitor the environment in order to find any patient lying on the floor. The system deals with various image-processing and sensor fusion techniques. The iWARD patient condition monitoring module evaluation tests were carried out in front of thirty healthcare professionals (doctors, nurses, nursing lecturers and healthcare assistances etc) during the final review meeting of the consortium and in two teaching hospitals (in Newcastle and San Sebastian, 2009) in Europe. The post iWARD system improved upon the prototype by adding a 3D laser sensor and replacing the original camera with a high quality Pan-Tilt-Zoom (PTZ) camera and implementing the identity detection methods. This allowed for the use of more robust patient condition monitoring algorithms. The outcomes of this research have significant contribution to the robotics application area in the hospital environment.

Index Terms—Intelligent system, patient condition monitoring, hospital robot.

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Cite: K. A. Mamun, A. Sharma, F. R. Islam, A. S. M. Hoque, T. Szecsi, "Patient Condition Monitoring Modular Hospital Robot," Journal of Software vol. 11, no. 8, pp. 768-786, 2016.