TY - JOUR
AU - Chen, Tao
AU - Schiek, Michael
AU - Dammers, Jürgen
AU - Shah, N. Jon
AU - van Waasen, Stefan
TI - Requirement-driven model-based development methodology applied to the design of a real-time MEG data processing unit
JO - Software and systems modeling
VL - 19
SN - 1619-1374
CY - New York, NY
PB - Springer
M1 - FZJ-2020-02791
SP - 1567–1587
PY - 2020
AB - The paper describes a multidisciplinary work that uses a model-based systems engineering method for developing real-time magnetoencephalography (MEG) signal processing. We introduce a requirement-driven, model-based development methodology (RDD and MBD) to provide a high-level environment and efficiently handle the complexity of computation and control systems. The proposed development methodology focuses on the use of System Modeling Language to define high-level model-based design descriptions for later implementation in heterogeneous hardware/software systems. The proposed approach was applied to the implementation of a real-time artifact rejection unit in MEG signal processing and demonstrated high efficiency in designing complex high-performance embedded systems. In MEG signal processing, biological artifacts in particular have a signal strength that overtop the signal of interest by orders of magnitude and must be removed from the measurement to achieve high-quality source reconstructions with minimal error contributions. However, many existing brain–computer interface studies overlook real-time artifact removal because of the demanding computational process. In this work, an automated real-time artifact rejection method is introduced, which is based on the recently presented method “ocular and cardiac artifact rejection for real-time analysis in MEG” (OCARTA). The method has been implemented using the RDD and MBD approach and successfully verified on a Virtex-6 field-programmable gate array.
LB - PUB:(DE-HGF)16
UR - <Go to ISI:>//WOS:000531132800001
DO - DOI:10.1007/s10270-020-00797-3
UR - https://juser.fz-juelich.de/record/878342
ER -