GT9: Games Robotics and smart technologies

Efthyvoulos Kyriacou's picture
Efthyvoulos Kyriacou
Evdokimos Konstantinidis's picture
Evdokimos Konstantinidis
Aristotle University of Thessaloniki (GR)
Conference room
Session time
Saturday, June 24, 2017 - 14:45 to 15:45
On supporting Parkinson's Disease patients: The i-PROGNOSIS Personalized Game Suite design approach
The use of serious games in health care interventions sector has grown rapidly in the last years, however, there is still a gap in the understanding on how these types of interventions are used for the management of the Parkinson Disease (PD), in particular. Targeting intelligent early detection and intervention in PD area, the Personalized Game Suite (PGS) design process approach is presented as part of the H2020 i-PROGNOSIS project that introduces the integration of different serious games in a unified platform (i.e., ExerGames, DietaryGames, EmoGames, and Handwriting/Voice Games).
S. B. Dias's picture
S. B. Dias
Evdokimos Konstantinidis's picture
Evdokimos Konstantinidis
Aristotle University of Thessaloniki (GR)
J. A. Diniz's picture
J. A. Diniz
Panagiotis Bamidis's picture
Panagiotis Bamidis
Aristotle University of Thessaloniki (GR)
V Charisis's picture
V Charisis
S Hadjidimitriou's picture
S Hadjidimitriou
M. Stadtschnitzer's picture
M. Stadtschnitzer
P. Fagerberg's picture
P. Fagerberg
Ioannis Ioakimidis's picture
Ioannis Ioakimidis
K Dimitropoulos's picture
K Dimitropoulos
N Grammalidis's picture
N Grammalidis
Leontios Hadjileontiadis's picture
Leontios Hadjileontiadis
Aristotle University of Thessaloniki (GR)
Carotid Bifurcation Plaque Stability Estimation based on Motion Analysis
"Through this study we are presenting the initial steps towards a real time motion analysis system to predict the stability of carotid bifurcation plaques. The analysis is performed on B-mode video loops. Loops are analyzed in order to follow systoly and diastoly sections of the cardiac cycle and trace the motion of plaques during these periods. We had created a system that applies Farneback’s optical flow estimation method in order to estimate the flow between consecutive frames or frames at a predefined interval.
Efthyvoulos Kyriacou's picture
Efthyvoulos Kyriacou
Andrew Nicolaides's picture
Andrew Nicolaides
Alexandra Constantinou's picture
Alexandra Constantinou
Maura Griffin's picture
Maura Griffin
Christos P Loizou's picture
Christos P Loizou
Cyprus University of Technology (CY)
Marios S. Pattichis's picture
Marios S. Pattichis
Hamed Nasrabadi's picture
Hamed Nasrabadi
Constantinos Pattichis's picture
Constantinos Pattichis
University of Cyprus (CY)
A Versatile Architecture for Building IoT Quantified-Self Applications
The abundance of activity trackers and biosignal sensors as well as the evolution of IoT and communication technologies have considerably advanced the concept of Quantified-Self. Nowadays there are several frameworks and applications that realize the concept, focusing though strictly on specific areas, from daily use to professional activities such as sport and healthcare. This work proposes a versatile, cross-domain solution for building quantified-self applications exploiting the capacities for open-design, modularity and extensibility of the AGILE IoT gateway.
Charalampos Doukas's picture
Charalampos Doukas
Panayiotis Tsanakas's picture
Panayiotis Tsanakas
Ilias Maglogiannis's picture
Ilias Maglogiannis
University of Piraeus (GR)
Commercial BCI Control And Functional Brain Networks in Spinal Cord Injury: A Proof-of-Concept.
Spinal Cord Injury (SCI), along with disability, results in changes of brain organization and structure. While sensorimotor networks of patients and healthy individuals share similar patterns, unique functional interactions have been identified in SCI networks. Brain-Computer Interfaces (BCIs) have emerged as a promising technology for movement restoration and rehabilitation of SCI patients. We describe an experimental methodology to combine high-resolution electroencephalography (EEG) for investigation of functional connectivity following SCI and non-invasive BCI control of robotic arms.
Alkinoos Athanasiou's picture
Alkinoos Athanasiou
Aristotle University of Thessaloniki (GR)
George Arfaras's picture
George Arfaras
Ioannis Xygonakis's picture
Ioannis Xygonakis
Panagiotis Kartsidis's picture
Panagiotis Kartsidis
Aristotle University of Thessaloniki (GR)
Niki Pandria's picture
Niki Pandria
Aristotle University of Thessaloniki (GR)
Kyriaki Rafailia Kavazidi's picture
Kyriaki Rafailia Kavazidi
Lab of Medical Physics The Medical School Aristotle University of Thessaloniki
Alexander Astaras's picture
Alexander Astaras
American College of Thessaloniki (GR)
Nicolas Foroglou's picture
Nicolas Foroglou
Konstantinos Polyzoidis's picture
Konstantinos Polyzoidis
Panagiotis Bamidis's picture
Panagiotis Bamidis
Aristotle University of Thessaloniki (GR)