Ambient assisted living (AAL) can be explained as the use of information and communication technologies (ICT) in a person's daily living and working environment to enable them to stay active longer, remain socially connected, and live independently into old age. AAL is strongly related to other concepts such as electronic health (e-health), mobile health (m-health), and smart health (s-health). AAL aims to provide assistive solutions for people with a wide range of physical, age-related, and cognitive challenges. AAL uses sensing technology embedded in objects, or in the environment or worn on the person to promote health and enhance well-being, or to help maintain an independent life at home and other context-aware environments. The data gathered by sensors is analysed to detect activity and infer knowledge about the physical, cognitive, or affective state of the person, recognising and classifying patterns, detecting trends and unusual or anomalous behaviour. Designing effective, usable, and intelligent interfaces for AAL systems requires understanding and supporting user cognitive and affective processes as well as the expression and perception of these processes in multiple modalities. The combination of computational intelligence methods with advanced software engineering technologies is crucial for handling a big amount of data of various types and origins and making AAL systems work efficiently.

This special issue will discuss and disseminate work on computational intelligence for ambient assisted living. Challenges include human behaviour analysis, modelling, and understanding, human activity recognition, and processing of sensor data. To address these challenges, we solicit high quality, original research articles.

Potential topics include, but are not limited to:

Intelligent and/or wearable sensors
Human behaviour analysis and activity recognition
Context-awareness and human-environment interaction
Affective and social computing for AAL
Nature-inspired intelligence methods
Multimodal user interfaces and agents for AAL systems
Internet-of-things for ambient assisted living
Advances in distributed systems and computing techniques for AAL
Applications of computational intelligence for data processing, objects modelling, positioning, and healthy habits fostering
Innovative software engineering methods for intelligent systems
Secure and private infrastructures for data gathering
Computational intelligence for e-health, m-health, and smart health
Security and privacy in body area networks for AAL
Privacy protection and anonymity for AAL
Intelligent user-centric infrastructure for AAL

Authors can submit their manuscripts via the Manuscript Tracking System at http://mts.hindawi.com/submit/journals/cin/ciaal/.

Lead Guest Editor
Robertas Damaševičius, Kaunas University of Technology, Kaunas, Lithuania

Guest Editors
Francisco Flórez-Revuelta, Kingston University, Surrey, UK
Agusti Solanas, Universitat Rovira i Virgili, Catalonia, Spain
Emiliano Tramontana, University of Catania, Catania, Italy
Marcin Woźniak, Silesian University of Technology, Gliwice, Poland