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dc.creatorMolina Cantero, Alberto Jesúses
dc.creatorCastro García, Juan Antonioes
dc.creatorLebrato Vázquez, Claraes
dc.creatorGómez González, Isabel Maríaes
dc.creatorMerino Monge, Manueles
dc.date.accessioned2018-05-22T05:54:12Z
dc.date.available2018-05-22T05:54:12Z
dc.date.issued2018
dc.identifier.citationMolina Cantero, A.J., Castro García, J.A., Lebrato-Vázquez, C., Gómez González, I.M. y Merino Monge, M. (2018). Real-Time Processing Library for Open-Source Hardware Biomedical Sensors. Sensors, 18 (4)
dc.identifier.issn1424-8220es
dc.identifier.urihttps://hdl.handle.net/11441/74878
dc.description.abstractApplications involving data acquisition from sensors need samples at a preset frequency rate, the filtering out of noise and/or analysis of certain frequency components. We propose a novel software architecture based on open-software hardware platforms which allows programmers to create data streams from input channels and easily implement filters and frequency analysis objects. The performances of the different classes given in the size of memory allocated and execution time (number of clock cycles) were analyzed in the low-cost platform Arduino Genuino. In addition, 11 people took part in an experiment in which they had to implement several exercises and complete a usability test. Sampling rates under 250 Hz (typical for many biomedical applications) makes it feasible to implement filters, sliding windows and Fourier analysis, operating in real time. Participants rated software usability at 70.2 out of 100 and the ease of use when implementing several signal processing applications was rated at just over 4.4 out of 5. Participants showed their intention of using this software because it was percieved as useful and very easy to use. The performances of the library showed that it may be appropriate for implementing small biomedical real-time applications or for human movement monitoring, even in a simple open-source hardware device like Arduino Genuino. The general perception about this library is that it is easy to use and intuitive.es
dc.formatapplication/pdfes
dc.language.isoenges
dc.publisherMDPIes
dc.relation.ispartofSensors, 18 (4)
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Estados Unidos de América*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectOpen-source hardwarees
dc.subjectDigital signal processinges
dc.subjectUsability testes
dc.subjectBiomedical applicationses
dc.subjectArduinoes
dc.titleReal-Time Processing Library for Open-Source Hardware Biomedical Sensorses
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Tecnología Electrónicaes
dc.relation.publisherversionhttp://www.mdpi.com/1424-8220/18/4/1033es
dc.identifier.doi10.3390/s18041033es
dc.contributor.groupUniversidad de Sevilla. TIC022: Tecnologías para la Asistencia, la Integración y la Saludes
idus.format.extent34es
dc.journaltitleSensorses
dc.publication.volumen18es
dc.publication.issue4es

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