guest ::
| Home > Publications database > Requirement-driven model-based development methodology applied to the design of a real-time MEG data processing unit > print |
| Home > Publications database > Requirement-driven model-based development methodology applied to the design of a real-time MEG data processing unit > print |
| 001 | 878342 | ||
| 005 | 20250129092507.0 | ||
| 024 | 7 | _ | |a 10.1007/s10270-020-00797-3 |2 doi |
| 024 | 7 | _ | |a 1619-1366 |2 ISSN |
| 024 | 7 | _ | |a 1619-1374 |2 ISSN |
| 024 | 7 | _ | |a 2128/25868 |2 Handle |
| 024 | 7 | _ | |a altmetric:83209296 |2 altmetric |
| 024 | 7 | _ | |a WOS:000531132800001 |2 WOS |
| 037 | _ | _ | |a FZJ-2020-02791 |
| 082 | _ | _ | |a 004 |
| 100 | 1 | _ | |a Chen, Tao |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Requirement-driven model-based development methodology applied to the design of a real-time MEG data processing unit |
| 260 | _ | _ | |a New York, NY |c 2020 |b Springer |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1602587499_2920 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a 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. |
| 536 | _ | _ | |a 573 - Neuroimaging (POF3-573) |0 G:(DE-HGF)POF3-573 |c POF3-573 |f POF III |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef |
| 700 | 1 | _ | |a Schiek, Michael |0 P:(DE-Juel1)133935 |b 1 |u fzj |
| 700 | 1 | _ | |a Dammers, Jürgen |0 P:(DE-Juel1)131757 |b 2 |u fzj |
| 700 | 1 | _ | |a Shah, N. Jon |0 P:(DE-Juel1)131794 |b 3 |u fzj |
| 700 | 1 | _ | |a van Waasen, Stefan |0 P:(DE-Juel1)142562 |b 4 |u fzj |
| 773 | _ | _ | |a 10.1007/s10270-020-00797-3 |0 PERI:(DE-600)2090971-8 |p 1567–1587 |t Software and systems modeling |v 19 |y 2020 |x 1619-1374 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/878342/files/Chen2020_Article_Requirement-drivenModel-basedD.pdf |
| 856 | 4 | _ | |y Published on 2020-05-08. Available in OpenAccess from 2021-05-08. |u https://juser.fz-juelich.de/record/878342/files/Chen-Tao-2020_postprint.pdf |
| 856 | 4 | _ | |y Published on 2020-05-08. Available in OpenAccess from 2021-05-08. |x pdfa |u https://juser.fz-juelich.de/record/878342/files/Chen-Tao-2020_postprint.pdf?subformat=pdfa |
| 856 | 4 | _ | |x pdfa |u https://juser.fz-juelich.de/record/878342/files/Chen2020_Article_Requirement-drivenModel-basedD.pdf?subformat=pdfa |
| 909 | C | O | |o oai:juser.fz-juelich.de:878342 |p openaire |p open_access |p VDB |p driver |p dnbdelivery |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 1 |6 P:(DE-Juel1)133935 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 2 |6 P:(DE-Juel1)131757 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 3 |6 P:(DE-Juel1)131794 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 4 |6 P:(DE-Juel1)142562 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Decoding the Human Brain |1 G:(DE-HGF)POF3-570 |0 G:(DE-HGF)POF3-573 |2 G:(DE-HGF)POF3-500 |v Neuroimaging |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |
| 914 | 1 | _ | |y 2020 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2020-01-14 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2020-01-14 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1160 |2 StatID |b Current Contents - Engineering, Computing and Technology |d 2020-01-14 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |d 2020-01-14 |
| 915 | _ | _ | |a Embargoed OpenAccess |0 StatID:(DE-HGF)0530 |2 StatID |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b SOFTW SYST MODEL : 2018 |d 2020-01-14 |
| 915 | _ | _ | |a DEAL Springer |0 StatID:(DE-HGF)3002 |2 StatID |d 2020-01-14 |w ger |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2020-01-14 |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0111 |2 StatID |b Science Citation Index Expanded |d 2020-01-14 |
| 915 | _ | _ | |a IF < 5 |0 StatID:(DE-HGF)9900 |2 StatID |d 2020-01-14 |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |d 2020-01-14 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2020-01-14 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2020-01-14 |
| 920 | _ | _ | |l yes |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-4-20090406 |k INM-4 |l Physik der Medizinischen Bildgebung |x 0 |
| 920 | 1 | _ | |0 I:(DE-Juel1)ZEA-2-20090406 |k ZEA-2 |l Zentralinstitut für Elektronik |x 1 |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-11-20170113 |k INM-11 |l Jara-Institut Quantum Information |x 2 |
| 920 | 1 | _ | |0 I:(DE-Juel1)VDB1046 |k JARA-BRAIN |l Jülich-Aachen Research Alliance - Translational Brain Medicine |x 3 |
| 980 | 1 | _ | |a FullTexts |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a I:(DE-Juel1)INM-4-20090406 |
| 980 | _ | _ | |a I:(DE-Juel1)ZEA-2-20090406 |
| 980 | _ | _ | |a I:(DE-Juel1)INM-11-20170113 |
| 980 | _ | _ | |a I:(DE-Juel1)VDB1046 |
| 981 | _ | _ | |a I:(DE-Juel1)PGI-4-20110106 |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|