@article{528e73e3d4ed4976a8f1841f7b09fd20,
title = "Data analysis from cognitive games interaction in Smart TV applications for patients with Parkinson's, Alzheimer's, and other types of dementia",
abstract = "Parkinson{\textquoteright}s disease and Alzheimer{\textquoteright}s disease are progressive nervous system disorders thataffect physical and cognitive capacities of individuals, including memory loss, motionimpairment, or problem-solving dysfunctions. Leisure activities are associated with reducingthe risk of dementia and are preventive policies for delaying the cognitive impairment inlater stages of those neurodegenerative diseases. Electronic games related to cognitive abil-ities are an easy and inexpensive alternative for stimulating brain activity in this kind ofpatients. The previous research demonstrated the acceptance of these activities in the envi-ronment of Connected TV when playing at home and in daily care centers. Interaction inConnected TV applications has its own particularities that influence the design of the inter-face, including the viewing distance, the type of interaction through a remote control orother techniques, the size of the screen, or the collectiveness of consumption. Iterative test-ing with patients of these groups revealed how the physical characteristics and cognitiveimpairment of these concrete end-users affect the human–computer interaction, offeringguidelines and recommendations in good practices for the Smart TV interface design. Onthe other hand, data analytics extracted from the interaction and evolution of the gameoffer important information enabling the creation of estimation prediction models aboutthe cognitive state of the patient.",
keywords = "AGE, Alzheimer's, Alzheimer's Disease, DESIGN, DISEASE, Data analysis, Digital Interaction, HCI, Human computer interaction, LEISURE ACTIVITIES, ONSET, PD, PEOPLE, Parkinson's, Parkinson's Disease, RISK, Smart TV, USABILITY, cognitive abilities, cognitive games, data analysis",
author = "Lopez, {Juan Pedro} and Francisco Moreno and Mirela Popa and Gustavo Hern{\'a}ndez-Pe{\~n}aloza and Federico {\'A}lvarez",
note = "Funding Information: This work has been partially supported by the EU project “ICT4LIFE: ICT services for Life Improvement for the Elderly” (ICT4LIFE Consortium, 2016 ). This project has received funding from the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No. 690090. The authors acknowledge patients, caregivers, and professionals, who disinterestedly participated in the different tests. Juan Pedro L{\'o}pez is a Telecommunication Engineer since 2007, he got the International Doctor's degree at Universidad Polit{\'e}cnica de Madrid in 2016 with his thesis focused on quality assessment for 2D and 3D stereoscopic video. His professional interests include video encoding, compression formats, high and ultra-high definition television, signal processing, and innovation that relates technology with environments such as accessibility, education, healthcare, and art. Since 2008, he complements teaching with working in national and international research projects about video encoding, quality of experience, broadcasting, accessibility, and HbbTV technologies. He got the Bachelor of History of Art at UNED University in 2017. Francisco Moreno received his BSc degree in Computer Science Engineering in 2008 on the Universidad Polit{\'e}cnica de Madrid. In 2007, he finished his final degree project called “Information Retrieval In Email Fields” on the Roskilde University (Denmark). From 2007 to 2012, he worked for different companies developing webs, where he got to be the Chief Developer in the advertisement agency SrBurns. He moved to the UK in 2012 where he worked 2 years and a half as a mobile developer. Since October 2015, he is working on the GATV group where he works developing webs and mobile apps in different research projects. Mirela Popa is a Postdoctoral Research Fellow in RAI in UM. She is working on the ICT4Life EU H2020 project, which advances methods for integrated care for the elderly, through ambient-assisted living. She completed her PhD at the Delft University of Technology, The Netherlands, and has worked as a research associate in the Intelligent and Interactive Systems (IIS) group at Innsbruck University, Austria. Her research interests lay in the areas of human behavior understanding, activity recognition, computer vision, machine learning, and data analysis and programming. Mirela is the author and co-author of more than 30 research, peer-reviewed papers. Gustavo Hern{\'a}ndez-Pe{\~n}aloza received the Telecom Engineer degree from Universidad Santo Tom{\'a}s, Colombia, in 2007, and the MSc degree in Telecommunication Technologies, System and Networks from the Universidad Polit{\'e}cnica de Valencia in 2009. He is currently pursuing a PhD degree at UPM. From 2010 to 2013, he was an Associate Research Fellow at the Universidad de Valencia (Spain). He is currently working with the research group in the Visual Telecommunications Applications Group, UPM. He has been participating with different technical developments in several Spanish and EU projects. His main topics include signal processing, wireless sensor networks, and machine learning. Federico {\'A}lvarez is a Telecom Engineer (2003) and receives PhD (2009), both by the Universidad Polit{\'e}cnica de Madrid. He is working as an Assistant Professor lecturing in UPM, and he develops his research within the GATV. He is nowadays the coordinator of EasyTV and FI-GLOBAL and a technical coordinator of ICT4LIFE in H2020. He has been in the last 10 years also leading the UPM participation in several EU-funded projects, such as the SEA, SIMPLE, AWISSENET, RESCUER, and FI-PPP project XIFI, and coordinated the projects nextMEDIA, INFINITY, and FI-LINKS. He is the author and co-author of (70+) papers in journals, congresses, and books. Publisher Copyright: {\textcopyright} Cambridge University Press 2019.",
year = "2019",
month = nov,
day = "1",
doi = "10.1017/S0890060419000386",
language = "English",
volume = "33",
pages = "442--457",
journal = "Ai Edam-Artificial Intelligence for Engineering Design Analysis and Manufacturing",
issn = "0890-0604",
publisher = "Cambridge University Press",
number = "4",
}