Contribution to a conference proceedings/Contribution to a book

FZJ-2020-02905

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Model-Driven Development Methodology Applied to Real-Time MEG Signal Preprocessing System Design

Chen, T. (Corresponding author)Extern*FZJ* ; Suslov, S.FZJ* ; Schiek, M.FZJ* ; Shah, N. J.FZJ* ; Waasen, S. v.FZJ* ; Dammers, J.FZJ*

2017
IEEE

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Please use a persistent id in citations: doi:10.1109/EMS.2017.16

Abstract: Model-based system engineering (MBSE) provides a high-level environment and efficiently handles the ever-rising complexity of computation and control systems. We introduce a requirement-driven, model-based development methodology (RDD & MBD) for real-time computation systems based on vendor neutral specifications. The proposed development methodology focuses on the use of Systems Modeling Language (SysML) to define high-level model-based design descriptions for later implementation in heterogeneous hardware/software systems. In magnetoencephalography (MEG) data processing, biological artifacts in particular overtop the signal of interest by orders of magnitude and must be removed from the measured signals to avoid reconstruction errors. However, many real-time brain computer interface (BCI) approaches neglect real-time artifact removal as it is computationally demanding. Therefore, we applied the RDD & MBD approach to the design of a system-on-chip (SoC), capable of performing real-time artifact rejection, based on the recently presented method 'Ocular and Cardiac Artifact rejection for Real-Time Analysis in MEG' (OCARTA).

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Contributing Institute(s):

1. Physik der Medizinischen Bildgebung (INM-4)
2. Jara-Institut Quantum Information (INM-11)
3. Jülich-Aachen Research Alliance - Translational Brain Medicine (JARA-BRAIN)
4. Zentralinstitut für Elektronik (ZEA-2)

Research Program(s):

1. 573 - Neuroimaging (POF3-573) (POF3-573)

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