title: On the use of Augmented Reality techniques in learning and interpretation of cardiologic data.
abstract: Augmented Reality is a technology which provides people with more intuitive ways of interaction and visualization, close to those in real world. The amount of applications using Augmented Reality is growing every day, and results can be already seen in several fields such as Education, Training, Entertainment and Medicine. The system proposed in this article intends to provide a friendly and intuitive interface based on Augmented Reality for heart beating evaluation and visualization. Cardiologic data is loaded from several distinct sources: simple standards of heart beating frequencies (for example situations like running or sleeping), files of heart beating signals, scanned electrocardiographs and real time data acquisition of patient's heart beating. All this data is processed to produce visualization within Augmented Reality environments. The results obtained in this research have shown that the developed system is able to simplify the understanding of concepts about heart beating and its functioning. Furthermore, the system can help health professionals in the task of retrieving, processing and converting data from all the sources handled by the system, with the support of an edition and visualization mode.
authors.affiliation: Virtual and Augmented Reality Research Group, Faculty of Electrical Engineering from Federal, University of Uberlândia-Brazil. lamounier@ufu.br
authors.forename: Edgard
authors.initials: E
authors.lastname: Lamounier
authors.forename: Arthur
authors.initials: A
authors.lastname: Bucioli
authors.forename: Alexandre
authors.initials: A
authors.lastname: Cardoso
authors.forename: Adriano
authors.initials: A
authors.lastname: Andrade
authors.forename: Alcimar
authors.initials: A
authors.lastname: Soares
mesh_terms: D000465:Algorithms; D003196:Computer Graphics; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D006801:Humans; D008955:Models, Cardiovascular; D012815:Signal Processing, Computer-Assisted; D014584:User-Computer Interface