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dc.contributor.authorSantamaría Vázquez, Eduardo
dc.contributor.authorMartínez Cagigal, Víctor 
dc.contributor.authorMarcos Martínez, Diego
dc.contributor.authorRodríguez Gonzílez, Víctor
dc.contributor.authorPérez Velasco, Sergio
dc.contributor.authorMoreno Calderón, Selene
dc.contributor.authorHornero Sánchez, Roberto 
dc.date.accessioned2023-01-18T12:56:19Z
dc.date.available2023-01-18T12:56:19Z
dc.date.issued2023
dc.identifier.citationComputer Methods and Programs in Biomedicine, 2023, vol. 230, 107357es
dc.identifier.issn0169-2607es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/58350
dc.descriptionProducción Científicaes
dc.description.abstractBackground and objective. Neurotechnologies have great potential to transform our society in ways that are yet to be uncovered. The rate of development in this field has increased significantly in recent years, but there are still barriers that need to be overcome before bringing neurotechnologies to the general public. One of these barriers is the difficulty of performing experiments that require complex software, such as brain-computer interfaces (BCI) or cognitive neuroscience experiments. Current platforms have limitations in terms of functionality and flexibility to meet the needs of researchers, who often need to implement new experimentation settings. This work was aimed to propose a novel software ecosystem, called MEDUSA©, to overcome these limitations. Methods. We followed strict development practices to optimize MEDUSA© for research in BCI and cognitive neuroscience, making special emphasis in the modularity, flexibility and scalability of our solution. Moreover, it was implemented in Python, an open-source programming language that reduces the development cost by taking advantage from its high-level syntax and large number of community packages. Results. MEDUSA© provides a complete suite of signal processing functions, including several deep learning architectures or connectivity analysis, and ready-to-use BCI and neuroscience experiments, making it one of the most complete solutions nowadays. We also put special effort in providing tools to facilitate the development of custom experiments, which can be easily shared with the community through an app market available in our website to promote reproducibility. Conclusions. MEDUSA© is a novel software ecosystem for modern BCI and neurotechnology experimentation that provides state-of-the-art tools and encourages the participation of the community to make a difference for the progress of these fields. Visit the official website at https://www.medusabci.com/ to know more about this project.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherElsevieres
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subject.classificationBrain–computer interfaceses
dc.subject.classificationNeurotechnologyes
dc.subject.classificationNeurosciencees
dc.subject.classificationElectroencephalography (EEG)es
dc.titleMEDUSA©: A novel Python-based software ecosystem to accelerate brain-computer interface and cognitive neuroscience researches
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2023 The Author(s)es
dc.identifier.doi10.1016/j.cmpb.2023.107357es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S016926072300024Xes
dc.identifier.publicationfirstpage107357es
dc.identifier.publicationtitleComputer Methods and Programs in Biomedicinees
dc.peerreviewedSIes
dc.description.projectMinisterio de Ciencia e Innovación/Agencia Estatal de Investigación/10.13039/501100011033/' y el Fondo Europeo de Desarrollo Regional (FEDER) grants (PID2020-115468RB-I00 and RTC2019-007350-1)es
dc.rightsAtribución 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones
dc.subject.unesco33 Ciencias Tecnológicases
dc.subject.unesco32 Ciencias Médicases


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