NDLI: Model development, testing and experimentation in a CyberWorkstation for Brain-Machine Interface research

Content Provider	IEEE Xplore Digital Library
Author	Rattanatamrong, P. Matsunaga, A. Raiturkar, P. Mesa, D. Ming Zhao Mahmoudi, B. DiGiovanna, J. Principe, J. Figueiredo, R. Sanchez, J. Fortes, J.
Copyright Year	2010
Description	Author affiliation: ETHZ, Zurich, Switzerland (DiGiovanna, J.) \|\| University of Florida, Gainesville, USA, 32610 (Rattanatamrong, P.; Matsunaga, A.; Raiturkar, P.; Mesa, D.; Mahmoudi, B.; Principe, J.; Figueiredo, R.; Sanchez, J.; Fortes, J.) \|\| Florida International University, USA (Ming Zhao)
Abstract	The CyberWorkstation (CW) is an advanced cyber-infrastructure for Brain-Machine Interface (BMI) research. It allows the development, configuration and execution of BMI computational models using high-performance computing resources. The CW's concept is implemented using a software structure in which an “experiment engine” is used to coordinate all software modules needed to capture, communicate and process brain signals and motor-control commands. A generic BMI-model template, which specifies a common interface to the CW's experiment engine, and a common communication protocol enable easy addition, removal or replacement of models without disrupting system operation. This paper reviews the essential components of the CW and shows how templates can facilitate the processes of BMI model development, testing and incorporation into the CW. It also discusses the ongoing work towards making this process infrastructure independent.
Starting Page	4339
Ending Page	4342
File Size	1014404
Page Count	4
File Format	PDF
ISBN	9781424441235
ISSN	1557170X
DOI	10.1109/IEMBS.2010.5626234
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-31
Publisher Place	Argentina
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Engines Mathematical model Computational modeling Brain modeling Algorithms Real time systems Testing
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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