scholarly journals The Future Role of High-Performance Computing in Cardiovascular Medicine and Science -Impact of Multi-Dimensional Data Analysis-

Author(s):  
Shinya Goto ◽  
Darren K. McGuire ◽  
Shinichi Goto
Computer ◽  
2013 ◽  
Vol 46 (5) ◽  
pp. 84-92 ◽  
Author(s):  
Amy F. Szczepanski ◽  
Jian Huang ◽  
Troy Baer ◽  
Yashema C. Mack ◽  
Sean Ahern

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Anton Umek ◽  
Anton Kos

This paper studies the main technological challenges of real-time biofeedback in sport. We identified communication and processing as two main possible obstacles for high performance real-time biofeedback systems. We give special attention to the role of high performance computing with some details on possible usage of DataFlow computing paradigm. Motion tracking systems, in connection with the biomechanical biofeedback, help in accelerating motor learning. Requirements about various parameters important in real-time biofeedback applications are discussed. Inertial sensor tracking system accuracy is tested in comparison with a high performance optical tracking system. Special focus is given on feedback loop delays. Real-time sensor signal acquisitions and real-time processing challenges, in connection with biomechanical biofeedback, are presented. Despite the fact that local processing requires less energy consumption than remote processing, many other limitations, most often the insufficient local processing power, can lead to distributed system as the only possible option. A multiuser signal processing in football match is recognised as an example for high performance application that needs high-speed communication and high performance remote computing. DataFlow computing is found as a good choice for real-time biofeedback systems with large data streams.


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