About the Project
visuAAL is a four-year (2020-2024) Marie Skłodowska-Curie Actions Innovative Training Network, funded by the European Union, that aims at bridging the knowledge gap between users’ requirements and the appropriate and secure use of video-based AAL technologies to deliver effective and supportive care to older adults managing their health and wellbeing.
visuAAL will seek to increase awareness and understanding of the context-specific ethical, legal, privacy and societal issues necessary to implement visual system across hospital, home and community settings, in a manner that protects and reassures users; outputs will stimulate the development of a new research perspective for constructively addressing privacy-aware video-based working solutions for assisted living.
visuAAL will provide a transdisciplinary and cross-sectoral combination of training, nonacademic placements, courses and workshops on scientific and complementary skills to 15 high achieving Early Stage Researchers (ESRs). These newly hired ESRs will contribute through their individual research projects to fulfil visuAAL's aims.
visuAAL brings together 5 universities:
• Chair of Communication Science, Human-Computer Interaction Center, RWTH Aachen University, Germany
• The Swedish Law and Informatics Research Institute (IRI), Stockholm University, Sweden
• The Trinity Centre for Practice and Healthcare Innovation, School of Nursing and Midwifery, Trinity College Dublin, Ireland
• Computer Vision Lab, TU Wien, Austria
• Department of Computing Technology, Universidad de Alicante, Spain (Project Coordinator)
This Consortium is complemented by 14 partner organizations from Austria, Germany, Ireland, Italy, Portugal, Spain, Sweden, and United Kingdom; that will contribute to the research and training activities.
For more information about visuAAL, see https://www.visuaal-itn.eu/
AI for dementia care
Although the progress and severity of dementia varies depending on the underlying cause (e.g. Alzheimer´s disease) there are common symptoms between the manifestations. These symptoms include personality changes, which manifests itself in becoming subdued or withdrawn. By using machine learning in long-term emotional analysis, it should be possible to recognize patterns and thus determine personality changes. In order to assign the person´s mood correctly, it is necessary that the algorithms treat the emotions context aware. This means that the current situation and environment of the person is detected (e.g. by sensors or smartphone) which allows to determine whether certain emotions are only felt in company or alone.
Development of new therapeutic intervention strategy. Behaviour analysis based on 3D and 2D tracking data in order to detect changes in the health status. Context aware recommendation for (music and dance) movements based on emotions and movement analysis. Empowerment of older people to increase the therapy effectiveness.
• Main Supervisor: Prof. Martin Kampel (TU-Wien)
• Second Supervisor: Prof J.M. Garcia (University of Alicante)
• Co-Supervisor: Prof R. Sablatnig (TU Wien)
• Advisor: Prof R. Bonsack (Universidade Católica Portuguesa) Dr. R. Planinc (Cogvis GMBH)
• Secondment 1: University of Alicante, (Supervisor F. Florez), M18-M20: Training and research on human computer interaction,
• Secondment 2: Universidade Catolica Poruguese, (Supervisor R. Bohnsack), M36-M38: Training on how to bring research to market.
Enrolment in Doctoral degree(s):
Doctoral Programme in Computer Science, Vienna University of Technology
How to apply?
Submit your application to https://www.visuaal-itn.eu/esr-vacancies. Please, ensure that you select vacancy number ESR12.
For questions related to this project proposal, please contact [Email Address Removed]
For all other questions, please use the following email address, clearly indicating the visuAAL vacancy number ESR12: [Email Address Removed]