Abstract

The use of computing technology to improve everyday life continues at an exponential rate. Computer technology is becoming an integral part of environments addressing important social and healthcare issues [1–5]. On the other hand, improving the quality of living environments to enable a person to reach his or her maximum potential becomes particularly important in an increasingly crowded and complex world in which inclusiveness and connectivity with the rest of the world are critical. Cognitive systems for assistive environments address the fact that people increasingly rely on technology in their own homes [6, 7] as well as in work environments. This special issue addresses aspects of intelligent and context-aware computer technology that is designed to assist persons with special needs. It focuses on the use of devices (e.g., different types of sensors), tools and methods that can monitor, assess and facilitate the functionality of a person’s everyday routine. By using, for example, camera-based sensors, touch sensors, heat sensors, in combination with special databases, personal area networks, machine learning and other computing methods, the aim is to achieve ubiquitous connectivity, distributed intelligence and interactivity through adaptive and easy-to-use interfaces. This special issue comes after the successful organization of the 3rd and 4th International Conferences on ‘‘PErvasive Technologies Related to Assistive Environments—PETRA 2010 and 2011,’’ which were held in Corfu and Herakleion, Greece (http://www.petrae.org/). This UAIS special issue is focused on research related to the design, development, evaluation and use of cognitive and context-aware systems for assistive environments, taking also into account the target audience of the UAIS Journal. As a result, nine (9) papers describing systems, algorithms and methodologies from the area of cognitive pervasive systems comprise the special issue. More specifically, Kwan et al. [8] in their paper propose interaction techniques that can be used with mousereplacement systems to enable the creation of accessible graphical user interfaces. To illustrate these techniques, they created Camera Canvas, an image editing application that uses a sliding toolbar as its universal menu controller. The parameters of the toolbar automatically adapt to the movement abilities of the specific user. During the experiments, the authors observed individuals with and without disabilities and of a variety of ages using Camera Canvas and found that the proposed techniques worked across many different movement abilities and experience levels. They also investigated how these techniques could be used to ‘‘retrofit’’ existing Windows applications with new graphical user interfaces and they created a tool called Menu Controller that can automatically re-render the menus of some existing applications into adaptive sliding toolbars. The Wang et al.’s [9] paper is in the field of human emotion detection utilizing facial expressions, a field considered important in a variety of pervasive applications in I. Maglogiannis (&) Department of Digital Systems, University of Piraeus, 80, Karaoli and Dimitriou Str, 185 34 Piraeus, Greece e-mail: imaglo@gmail.com; imaglo@unipi.gr

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