Turning Homes into Low-Cost Ambient Assisted Living Environments

Alexiei Dingli, Daniel Attard and Ruben Mamo
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Alexiei Dingli: University of Malta, Malta
Daniel Attard: University of Malta, Malta
Ruben Mamo: University of Malta, Malta

International Journal of Ambient Computing and Intelligence (IJACI), 2012, vol. 4, issue 2, 1-23

Abstract: Today motion recognition has become more popular in areas like health care. In real-time environments, the amount of information and data required to compute the user’s motion is substantial, while the time to collect and process this information are crucial parameters in the performance of a motion recognition system. The nature of the data determines the design of the system. One important aspect of this system is reducing the delay between sensing and recognising a motion, while achieving acceptable levels of accuracy. The detection of humans in images is a challenging problem. In this paper, the authors present a solution using the Kinect, a motion sensing input device by Microsoft designed for the Xbox 360 console, to create an Ambient Assisted Living (AAL) application which monitors a person’s position, labels objects around a room, takes voice input, and raises alerts in case of falls. The authors present a number of modules like converting Kinect Skeletal Data to allow mouse control via hand movement, building a Finite State Machine (FSM), obtaining pose information, voice commands to allow interaction with the application, and face detection and recognition. The authors use different algorithms to achieve the required outcome.

Date: 2012
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