Enabling Model-Based Design for Real-Time Spike Detection

Goal : This study addresses the inherent difficulties in the creation of neuroengineering devices for real-time neural signal processing, a task typically characterized by intricate and technically demanding processes. Beneath the substantial hardware advancements in neurotechnology, there is often...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE open journal of engineering in medicine and biology Vol. 6; pp. 312 - 319
Main Authors:	Di Florio, Mattia, Bornat, Yannick, Care, Marta, Rosa Cota, Vinicius, Buccelli, Stefano, Chiappalone, Michela
Format:	Journal Article
Language:	English
Published:	United States IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Codes Computational modeling Computer architecture Data processing Design Field programmable gate arrays Field-Programmable Gate Array (FPGA) Hardware Hardware description languages Hardware design languages HDL coder High density lipoprotein in vivo experiments Information processing Integrated circuits Latency Neural engineering neuroengineering Prototyping Real time Signal processing Signal processing algorithms Software packages Source code Workflow Signal processing Field-Programmable Gate Array (FPGA) neuroengineering in vivo experiments HDL coder
ISSN:	2644-1276, 2644-1276
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	Goal : This study addresses the inherent difficulties in the creation of neuroengineering devices for real-time neural signal processing, a task typically characterized by intricate and technically demanding processes. Beneath the substantial hardware advancements in neurotechnology, there is often rather complex low-level code that poses challenges in terms of development, documentation, and long-term maintenance. Methods : We adopted an alternative strategy centered on Model-Based Design (MBD) to simplify the creation of neuroengineering systems and reduce the entry barriers. MBD offers distinct advantages by streamlining the design workflow, from modelling to implementation, thus facilitating the development of intricate systems. A spike detection algorithm has been implemented on a commercially available system based on a Field-Programmable Gate Array (FPGA) that combines neural probe electronics with configurable integrated circuit. The entire process of data handling and data processing was performed within the Simulink environment, with subsequent generation of hardware description language (HDL) code tailored to the FPGA hardware. Results : The validation was conducted through in vivo experiments involving six animals and demonstrated the capability of our MBD-based real time processing (latency <= 100.37 µs) to achieve the same performances of offline spike detection. Conclusions : This methodology can have a significant impact in the development of neuroengineering systems by speeding up the prototyping of various system architectures. We have made all project code files open source, thereby providing free access to fellow scientists interested in the development of neuroengineering systems.
AbstractList	Goal : This study addresses the inherent difficulties in the creation of neuroengineering devices for real-time neural signal processing, a task typically characterized by intricate and technically demanding processes. Beneath the substantial hardware advancements in neurotechnology, there is often rather complex low-level code that poses challenges in terms of development, documentation, and long-term maintenance. Methods : We adopted an alternative strategy centered on Model-Based Design (MBD) to simplify the creation of neuroengineering systems and reduce the entry barriers. MBD offers distinct advantages by streamlining the design workflow, from modelling to implementation, thus facilitating the development of intricate systems. A spike detection algorithm has been implemented on a commercially available system based on a Field-Programmable Gate Array (FPGA) that combines neural probe electronics with configurable integrated circuit. The entire process of data handling and data processing was performed within the Simulink environment, with subsequent generation of hardware description language (HDL) code tailored to the FPGA hardware. Results : The validation was conducted through in vivo experiments involving six animals and demonstrated the capability of our MBD-based real time processing (latency <= 100.37 µs) to achieve the same performances of offline spike detection. Conclusions : This methodology can have a significant impact in the development of neuroengineering systems by speeding up the prototyping of various system architectures. We have made all project code files open source, thereby providing free access to fellow scientists interested in the development of neuroengineering systems. Goal: This study addresses the inherent difficulties in the creation of neuroengineering devices for real-time neural signal processing, a task typically characterized by intricate and technically demanding processes. Beneath the substantial hardware advancements in neurotechnology, there is often rather complex low-level code that poses challenges in terms of development, documentation, and long-term maintenance. Methods: We adopted an alternative strategy centered on Model-Based Design (MBD) to simplify the creation of neuroengineering systems and reduce the entry barriers. MBD offers distinct advantages by streamlining the design workflow, from modelling to implementation, thus facilitating the development of intricate systems. A spike detection algorithm has been implemented on a commercially available system based on a Field-Programmable Gate Array (FPGA) that combines neural probe electronics with configurable integrated circuit. The entire process of data handling and data processing was performed within the Simulink environment, with subsequent generation of hardware description language (HDL) code tailored to the FPGA hardware. Results: The validation was conducted through in vivo experiments involving six animals and demonstrated the capability of our MBD-based real time processing (latency <= 100.37 µs) to achieve the same performances of offline spike detection. Conclusions: This methodology can have a significant impact in the development of neuroengineering systems by speeding up the prototyping of various system architectures. We have made all project code files open source, thereby providing free access to fellow scientists interested in the development of neuroengineering systems.Goal: This study addresses the inherent difficulties in the creation of neuroengineering devices for real-time neural signal processing, a task typically characterized by intricate and technically demanding processes. Beneath the substantial hardware advancements in neurotechnology, there is often rather complex low-level code that poses challenges in terms of development, documentation, and long-term maintenance. Methods: We adopted an alternative strategy centered on Model-Based Design (MBD) to simplify the creation of neuroengineering systems and reduce the entry barriers. MBD offers distinct advantages by streamlining the design workflow, from modelling to implementation, thus facilitating the development of intricate systems. A spike detection algorithm has been implemented on a commercially available system based on a Field-Programmable Gate Array (FPGA) that combines neural probe electronics with configurable integrated circuit. The entire process of data handling and data processing was performed within the Simulink environment, with subsequent generation of hardware description language (HDL) code tailored to the FPGA hardware. Results: The validation was conducted through in vivo experiments involving six animals and demonstrated the capability of our MBD-based real time processing (latency <= 100.37 µs) to achieve the same performances of offline spike detection. Conclusions: This methodology can have a significant impact in the development of neuroengineering systems by speeding up the prototyping of various system architectures. We have made all project code files open source, thereby providing free access to fellow scientists interested in the development of neuroengineering systems. : This study addresses the inherent difficulties in the creation of neuroengineering devices for real-time neural signal processing, a task typically characterized by intricate and technically demanding processes. Beneath the substantial hardware advancements in neurotechnology, there is often rather complex low-level code that poses challenges in terms of development, documentation, and long-term maintenance. : We adopted an alternative strategy centered on Model-Based Design (MBD) to simplify the creation of neuroengineering systems and reduce the entry barriers. MBD offers distinct advantages by streamlining the design workflow, from modelling to implementation, thus facilitating the development of intricate systems. A spike detection algorithm has been implemented on a commercially available system based on a Field-Programmable Gate Array (FPGA) that combines neural probe electronics with configurable integrated circuit. The entire process of data handling and data processing was performed within the Simulink environment, with subsequent generation of hardware description language (HDL) code tailored to the FPGA hardware. : The validation was conducted through in vivo experiments involving six animals and demonstrated the capability of our MBD-based real time processing (latency <= 100.37 µs) to achieve the same performances of offline spike detection. : This methodology can have a significant impact in the development of neuroengineering systems by speeding up the prototyping of various system architectures. We have made all project code files open source, thereby providing free access to fellow scientists interested in the development of neuroengineering systems.
Author	Care, Marta Di Florio, Mattia Bornat, Yannick Chiappalone, Michela Rosa Cota, Vinicius Buccelli, Stefano
Author_xml	– sequence: 1 givenname: Mattia orcidid: 0000-0002-5263-1133 surname: Di Florio fullname: Di Florio, Mattia email: Mattia.Diflorio@edu.unige.it organization: Department of Informatics, Bioengineering, Robotics, System Engineering (DIBRIS), University of Genova, Genova, Italy – sequence: 2 givenname: Yannick surname: Bornat fullname: Bornat, Yannick email: yannick.bornat@ims-bordeaux.fr organization: Laboratoire de l'Intégration du Matériau au Système (IMS), University of Bordeaux, Bordeaux INP, CNRS UMR 5218, Talence Cedex, France – sequence: 3 givenname: Marta surname: Care fullname: Care, Marta email: marta.care@hsanmartino.it organization: IRCCS Ospedale Policlinico San Martino, Genova, Italy – sequence: 4 givenname: Vinicius orcidid: 0000-0002-2338-5949 surname: Rosa Cota fullname: Rosa Cota, Vinicius email: Vinicius.RosaCota@iit.it organization: Rehab Technologies Lab, Istituto Italiano di Tecnologia, Genova, Italy – sequence: 5 givenname: Stefano surname: Buccelli fullname: Buccelli, Stefano email: stefano.buccelli@gmail.com organization: Rehab Technologies Lab, Istituto Italiano di Tecnologia, Genova, Italy – sequence: 6 givenname: Michela orcidid: 0000-0003-1427-5147 surname: Chiappalone fullname: Chiappalone, Michela email: michela.chiappalone@unige.it organization: Department of Informatics, Bioengineering, Robotics, System Engineering (DIBRIS), University of Genova, Genova, Italy
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/40657055$$D View this record in MEDLINE/PubMed
BookMark	eNpdkUtPGzEUhS0EKo_yB1BVjdRNN5P6_VgWGloQCAno2vLjTuR0Mk7tyaL_vhOSItSVLd_vHJ3rc4oOhzwAQhcEzwjB5svD7fz-ckYxFTMmmFJSH6ATKjlvCVXy8M39GJ3XusR4QgkhVL9DxxxLobAQJ8jMB-f7NCya-xyhby9dhdh8g5oWQ9Pl0jyC69vntILmaZ1-wTQaIYwpD-_RUef6Cuf78wz9vJ4_X_1o7x6-31x9vWsDJ2Jsg-esk1Jo8NwE3wVHsPTegwOiIiHMK-kdcBU1VZQw6LRgMQgTXWAGDDtDNzvfmN3SrktaufLHZpfsy0MuC-vKmEIPNnRMCk-14yFyDdIoAxCBUEmNJgEmr887r3XJvzdQR7tKNUDfuwHyplpGqTFYYYMn9NN_6DJvyjBtahlRXGtN5Tbcxz218SuIr_H-ffAE0B0QSq61QPeKEGy3RdqXIu22SLsvchJ92IkSALwRaIWxkewv3f6WTg
CODEN	IOJEA7
Cites_doi	10.1088/1741-2552/accece 10.23919/FPL.2017.8056858 10.1038/nature24636 10.3389/fneur.2018.00212 10.1016/j.brs.2017.11.016 10.1038/496159a 10.1109/ReConFig.2012.6416762 10.1073/pnas.1316885110 10.1109/DDECS.2012.6219090 10.1016/j.bios.2018.10.032 10.1016/j.jneumeth.2013.01.026 10.1109/TBCAS.2018.2830659 10.3390/brainsci12111578 10.1016/j.brainresbull.2015.04.007 10.1088/1741-2552/ab3319 10.1126/sciadv.adf9524 10.1177/2398212818776475 10.1126/science.abf4588 10.3389/fnins.2018.00026 10.1109/SPL.2011.5782635 10.1126/scitranslmed.abj1441 10.1088/1741-2552/aa654b 10.1038/511018a 10.3390/electronics7120392 10.1162/089976604774201631 10.3390/digital1010003 10.1088/1741-2552/acc7cc 10.1109/ICCAD.2013.6691099 10.1109/MSPEC.2015.7024509 10.1109/EMBC48229.2022.9871444 10.1016/j.neuron.2022.05.007
ContentType	Journal Article
Copyright	2025 The Authors. Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2025
Copyright_xml	– notice: 2025 The Authors. – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2025
DBID	97E ESBDL RIA RIE AAYXX CITATION NPM 7QO 8FD FR3 K9. P64 7X8 DOA
DOI	10.1109/OJEMB.2025.3537768
DatabaseName	IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE Xplore Open Access Journals IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef PubMed Biotechnology Research Abstracts Technology Research Database Engineering Research Database ProQuest Health & Medical Complete (Alumni) Biotechnology and BioEngineering Abstracts MEDLINE - Academic Directory of Open Access Journals (DOAJ)
DatabaseTitle	CrossRef PubMed ProQuest Health & Medical Complete (Alumni) Engineering Research Database Biotechnology Research Abstracts Technology Research Database Biotechnology and BioEngineering Abstracts MEDLINE - Academic
DatabaseTitleList	ProQuest Health & Medical Complete (Alumni) MEDLINE - Academic PubMed
Database_xml	– sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 3 dbid: RIE name: IEEE Xplore url: https://ieeexplore.ieee.org/ sourceTypes: Publisher – sequence: 4 dbid: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering
EISSN	2644-1276
EndPage	319
ExternalDocumentID	oai_doaj_org_article_cf365b28a4cd48e6979eede1262981ce 40657055 10_1109_OJEMB_2025_3537768 10870096
Genre	orig-research Journal Article
GrantInformation_xml	– fundername: European UnionNextGenerationEU and by the Ministry of University and Research – fundername: RAISE Innovation Ecosystem – fundername: National Recovery and Resilience Plan
GroupedDBID	0R~ 97E AAJGR ABAZT ABVLG ALMA_UNASSIGNED_HOLDINGS BEFXN BFFAM BGNUA BKEBE BPEOZ EBS ESBDL GROUPED_DOAJ JAVBF M~E OCL OK1 PGMZT RIA RIE RPM AAYXX CITATION NPM 7QO 8FD FR3 K9. P64 7X8
ID	FETCH-LOGICAL-c415t-cb43f6658eb49cbfca106bbbeae17d113b76bae47d827213ef853dc59dac39e93
IEDL.DBID	RIE
ISICitedReferencesCount	1
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001439380100001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	2644-1276
IngestDate	Fri Oct 03 12:50:52 EDT 2025 Mon Jul 14 20:49:59 EDT 2025 Tue Oct 07 07:12:20 EDT 2025 Thu Jul 17 02:06:57 EDT 2025 Sat Nov 29 08:10:02 EST 2025 Wed Aug 27 01:43:36 EDT 2025
IsDoiOpenAccess	true
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Keywords	Signal processing Field-Programmable Gate Array (FPGA) neuroengineering in vivo experiments HDL coder
Language	English
License	https://creativecommons.org/licenses/by/4.0/legalcode 2025 The Authors.
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c415t-cb43f6658eb49cbfca106bbbeae17d113b76bae47d827213ef853dc59dac39e93
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
ORCID	0000-0002-5263-1133 0000-0003-1427-5147 0000-0002-2338-5949
OpenAccessLink	https://ieeexplore.ieee.org/document/10870096
PMID	40657055
PQID	3174888269
PQPubID	5075789
PageCount	8
ParticipantIDs	doaj_primary_oai_doaj_org_article_cf365b28a4cd48e6979eede1262981ce pubmed_primary_40657055 crossref_primary_10_1109_OJEMB_2025_3537768 proquest_journals_3174888269 ieee_primary_10870096 proquest_miscellaneous_3229907090
PublicationCentury	2000
PublicationDate	20250000 2025-00-00 20250101 2025-01-01
PublicationDateYYYYMMDD	2025-01-01
PublicationDate_xml	– year: 2025 text: 20250000
PublicationDecade	2020
PublicationPlace	United States
PublicationPlace_xml	– name: United States – name: New York
PublicationTitle	IEEE open journal of engineering in medicine and biology
PublicationTitleAbbrev	OJEMB
PublicationTitleAlternate	IEEE Open J Eng Med Biol
PublicationYear	2025
Publisher	IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml	– name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References	ref13 ref12 ref15 ref14 ref31 ref30 ref11 ref10 Car (ref19) ref32 ref2 ref1 ref17 ref16 ref18 ref24 ref23 ref26 ref25 ref20 ref22 ref21 ref28 ref27 ref29 ref8 ref7 ref9 ref4 ref3 ref6 ref5
References_xml	– ident: ref28 doi: 10.1088/1741-2552/accece – ident: ref15 doi: 10.23919/FPL.2017.8056858 – ident: ref30 doi: 10.1038/nature24636 – ident: ref5 doi: 10.3389/fneur.2018.00212 – ident: ref13 doi: 10.1016/j.brs.2017.11.016 – ident: ref6 doi: 10.1038/496159a – ident: ref29 doi: 10.1109/ReConFig.2012.6416762 – ident: ref11 doi: 10.1073/pnas.1316885110 – ident: ref32 doi: 10.1109/DDECS.2012.6219090 – ident: ref4 doi: 10.1016/j.bios.2018.10.032 – ident: ref22 doi: 10.1016/j.jneumeth.2013.01.026 – ident: ref26 doi: 10.1109/TBCAS.2018.2830659 – ident: ref1 doi: 10.3390/brainsci12111578 – start-page: 1 volume-title: Proc. 8th Congr. Nat. Group Bioeng. ident: ref19 article-title: Towards personalized electroceutical therapy: Electrophysiological investigations in a pre-clinical model of ischemic lesion – ident: ref25 doi: 10.1016/j.brainresbull.2015.04.007 – ident: ref21 doi: 10.1088/1741-2552/ab3319 – ident: ref2 doi: 10.1126/sciadv.adf9524 – ident: ref8 doi: 10.1177/2398212818776475 – ident: ref3 doi: 10.1126/science.abf4588 – ident: ref10 doi: 10.3389/fnins.2018.00026 – ident: ref14 doi: 10.1109/SPL.2011.5782635 – ident: ref12 doi: 10.1126/scitranslmed.abj1441 – ident: ref17 doi: 10.1088/1741-2552/aa654b – ident: ref7 doi: 10.1038/511018a – ident: ref24 doi: 10.3390/electronics7120392 – ident: ref20 doi: 10.1162/089976604774201631 – ident: ref23 doi: 10.3390/digital1010003 – ident: ref27 doi: 10.1088/1741-2552/acc7cc – ident: ref16 doi: 10.1109/ICCAD.2013.6691099 – ident: ref9 doi: 10.1109/MSPEC.2015.7024509 – ident: ref18 doi: 10.1109/EMBC48229.2022.9871444 – ident: ref31 doi: 10.1016/j.neuron.2022.05.007
SSID	ssj0002511128
Score	2.2853656
Snippet	Goal : This study addresses the inherent difficulties in the creation of neuroengineering devices for real-time neural signal processing, a task typically... : This study addresses the inherent difficulties in the creation of neuroengineering devices for real-time neural signal processing, a task typically... Goal: This study addresses the inherent difficulties in the creation of neuroengineering devices for real-time neural signal processing, a task typically...
SourceID	doaj proquest pubmed crossref ieee
SourceType	Open Website Aggregation Database Index Database Publisher
StartPage	312
SubjectTerms	Algorithms Codes Computational modeling Computer architecture Data processing Design Field programmable gate arrays Field-Programmable Gate Array (FPGA) Hardware Hardware description languages Hardware design languages HDL coder High density lipoprotein in vivo experiments Information processing Integrated circuits Latency Neural engineering neuroengineering Prototyping Real time Signal processing Signal processing algorithms Software packages Source code Workflow
SummonAdditionalLinks	– databaseName: Directory of Open Access Journals (DOAJ) dbid: DOA link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Lb9QwEB6higMcEI8CoQUFiRsyTewkto8sbIUQFMRD6s3yYyxVoLRqt_z-zjjZVS6IC7cothzrm3jmm8TzGeBVGpLOIfYiYOdFJ1EJjxlF6FkbppVDMqVQ-JM-OTGnp_br4qgv3hM2yQNPwB3FrIY-SOO7mDqDg9WW3DrSKNKaNiJ7X2I9i2SKfTATZ_K82yqZxh59-bj-vKJ8UPZvVK-0Zm3VRSQqgv3zCSt_J5sl6Bzfh3szW6zfTrN8ALdwfAh3FxqCj8CuufqJLms-1uy3WFFYSvX7sjGjJkZafyMqKLjSo_5-cfYLqWlTtl-N-_DzeP3j3Qcxn4cgIoXZjYihU3kgyoChszHk6CmfCyGgx1antlVBD8Fjp5ORlNgpzBSLU-xt8lFZtOox7I3nIz6F2uRGZRmljF53aGKISQ1KBqJ72RszVPB6i427mGQvXEkXGusKko6RdDOSFawYvl1PlqwuN8iQbjak-5chK9hn8BePI1dCCVYFh1truHl9XTliPeR5KDWyFbzcNdPK4N8dfsTza-ojOdTqxjYVPJmsuBucaEzPOkLP_sfMD-AOozF9mDmEvc3lNT6H2_HP5uzq8kV5MW8Asbrkwg priority: 102 providerName: Directory of Open Access Journals
Title	Enabling Model-Based Design for Real-Time Spike Detection
URI	https://ieeexplore.ieee.org/document/10870096 https://www.ncbi.nlm.nih.gov/pubmed/40657055 https://www.proquest.com/docview/3174888269 https://www.proquest.com/docview/3229907090 https://doaj.org/article/cf365b28a4cd48e6979eede1262981ce
Volume	6
WOSCitedRecordID	wos001439380100001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVAON databaseName: DOAJ Directory of Open Access Journals customDbUrl: eissn: 2644-1276 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0002511128 issn: 2644-1276 databaseCode: DOA dateStart: 20200101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources customDbUrl: eissn: 2644-1276 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0002511128 issn: 2644-1276 databaseCode: M~E dateStart: 20200101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lb9QwEB7RigMceBYaWlZB6g25JHYS20e2bIUQfaiAtDfLj7FUUWWrdpcjv52xk13tpQcukRVbeXye8Xxje8YAR6ELMjrfMoeNZQ1HwSxGZK5NuWFq3gWVA4W_y_NzNZ_ryzFYPcfCIGLefIbHqZjX8sPCr9JUGWk4SRdx7h3YkVIOwVqbCZXElWmwXQfGVPrTxbfZ2ZRcQN4ei1ZImdKpbhmfnKN_PFTlYX6Z7czp8__8whfwbCSU5edBAl7CI-xfwdOtNIOvQc9SgBQVy3Ty2Q2bkuUK5Ze8d6Mk0lpeEVtkKRik_HF7_Rupapl3aPV78Ot09vPkKxuPTGCeLPGSedeI2BGrQNdo76K35PI559BiLUNdCyc7Z7GRQXHy_QRGMtfBtzpYLzRq8QZ2-0WP-1CqWInIPefeygaVdz6ITnBHjDBapboCPq6xNLdDZgyTPYpKm4y8ScibEfkCpgnuTcuU1TrfIPjMqCTGR9G1jivb-NAo7LTUZMKRJIZrVXssYC9BvvW6Ae0CDte9Z0YVvDdEjGhwIu9JF_BhU03Kk1ZEbI-LFbXhyRrLSlcFvB16ffNwYjptSjX07oGXHsCT9IPDdMwh7C7vVvgeHvs_y-v7uwlJ6FxNsodP17O_s0mW1n8RmOTb
linkProvider	IEEE
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lb9QwEB5BQQIOPEsbKBAkbihtYjuxfWRhqwLbBUGRerP8GEsVKFu1u_x-xk52tZceuFmxFSefZzzf2J4xwLvQBRmdbyuHwlaCIa8sRqxcm3LDNKwLKgcKz-R8rs7P9fcxWD3HwiBiPnyGh6mY9_LDwq_SUhlpOEkXce7bcKcVgjVDuNZmSSWxZZpu16ExtT769mV6OiEnkLWHvOVSpoSqW-YnZ-kfr1W5mWFmS3P86D-_8TE8HCll-WGQgSdwC_un8GAr0eAz0NMUIkXFMt199qeakO0K5ad8eqMk2lr-IL5YpXCQ8uflxW-kqmU-o9Xvwq_j6dnHk2q8NKHyZIuXlXeCx454BTqhvYvektPnnEOLjQxNw53snEUhg2Lk_XGMZLCDb3WwnmvU_Dns9Ise96FUseaReca8lQKVdz7wjjNHnDBapboC3q-xNJdDbgyTfYpam4y8ScibEfkCJgnuTcuU1zo_IPjMqCbGR961jikrfBAKOy01GXEkmWFaNR4L2E2Qb3U3oF3AwXr0zKiE14aoEU1P5D_pAt5uqkl90p6I7XGxojYs2WNZ67qAvWHUNy8nrtOmZEMvbuj0Ddw7OTudmdnn-deXcD_97LA4cwA7y6sVvoK7_u_y4vrqdZbTf_zp5RQ
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Enabling+Model-Based+Design+for+Real-Time+Spike+Detection&rft.jtitle=IEEE+open+journal+of+engineering+in+medicine+and+biology&rft.au=Di+Florio%2C+Mattia&rft.au=Bornat%2C+Yannick&rft.au=Care%2C+Marta&rft.au=Rosa+Cota%2C+Vinicius&rft.date=2025&rft.pub=IEEE&rft.eissn=2644-1276&rft.volume=6&rft.spage=312&rft.epage=319&rft_id=info:doi/10.1109%2FOJEMB.2025.3537768&rft.externalDocID=10870096
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2644-1276&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2644-1276&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2644-1276&client=summon