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Open access

Christopher Armstrong, Diarmuid Kavanagh, Sara Lal and Peter Rossiter

Combining Popular Game Consoles and OSGi to Investigate Autonomous In-The-Field Biomedical Data Acquisition and Management

The need and interest in conducting biomedical research outside the traditional laboratory is increasing. In the field testing such as in the participant's home or work environment is a growing consideration when undertaking biomedical investigation. This type of research requires at a minimum semi-autonomous computer systems that collect such data and send it back to the laboratory for processing and dissemination with the smallest amount of attendance by the participant or even the experimenter. A key aspect of supporting this type of research is the selection of the appropriate software and hardware components. These supporting systems need to be reliable, allow considerable customizability and be readily accessible but also able to be locked down. In this paper we report a set of requirements for the hardware and software for such a system. We then utilise these requirements to evaluate the use of game consoles as a hardware platform in comparison to other hardware choices. We finish by outline one particular aspect of the supporting software used to support the chosen hardware platform based on the OSGi framework.

Open access

Mitesh Patel, Sara Lal, Diarmuid Kavanagh and Peter Rossiter

Fatigue Detection Using Computer Vision

Long duration driving is a significant cause of fatigue related accidents of cars, airplanes, trains and other means of transport. This paper presents a design of a detection system which can be used to detect fatigue in drivers. The system is based on computer vision with main focus on eye blink rate. We propose an algorithm for eye detection that is conducted through a process of extracting the face image from the video image followed by evaluating the eye region and then eventually detecting the iris of the eye using the binary image. The advantage of this system is that the algorithm works without any constraint of the background as the face is detected using a skin segmentation technique. The detection performance of this system was tested using video images which were recorded under laboratory conditions. The applicability of the system is discussed in light of fatigue detection for drivers.