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BackgroundBecause of the demographic change in industrial countries new technical solutions for the independent living of elderly will become important in the next years. Ambient Assisted Living seeks to address the upcoming challenges by providing technical aids for elderly and care givers. Therefore it is crucial to understand how those socio-technical solutions can address their needs and quality of life (QOL). The aim of this study was to analyse the main needs of dependent elderly and to investigate how different solutions can contribute to health and quality of life.MethodsA qualitative study design consisting of interviews with 11 professionals of geriatric care organisations was chosen. The data analysis was done by applying the qualitative content analysis by Philipp Mayring. The analysis was based on the basic principle of the bio-psycho-social model of healthResultsAmbient Assisted Living solutions and assistive technologies can have positive impacts on different dimensions of health and quality of life. The needs and problems of elderly can be addressed by applying appropriate solutions which influence the physical, mental and social dimensions of quality of life. There are also benefits for social care providers, their staff and caring relatives of impaired elderly. Ambient Assisted Living solutions can also be used as a facilitator for operational optimization of care services.ConclusionsSolutions for telemedicine and telecare which are connected to Ambient Assisted Living solutions will have the biggest positive impact on care giving services. Also simple technical aids can be beneficial for elderly to enhance QOL by enabling autonomy in their familiar surroundings.

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This work describes a modular open source AAL framework for event recognition and smart home control. Various integrated tools simplify the configuration task, the personalization as well as the learning of activity models by a novel approach. Flexibility, standard compliant interfaces as well as the ability to transfer the system into new environments with little efforts have a strong focus. The paper describes the system architecture and the algorithms used.

The setup of a human computer interaction electrooculography (EOG) measurement trail for developing pattern recognition algorithms is described. With an easy to wear EOG measurement device we relized performance tests with a group of normal individuals as well as with one individual suffering from multiple sclerosis (MS). The individuals had to perform different eye movement patterns for coding information to control the environment. Different patterns of recognition in the time domain have been tried and implemented to perform online performance tests. The aim is to develop an EOG based communication device passed on pattern recognition algorithms for user with limited functionality.