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dc.contributor.authorMugruza-Vassallo, Carlos
dc.contributor.otherMugruza-Vassallo, Carlos
dc.date.accessioned2017-07-19T17:57:11Z
dc.date.available2017-07-19T17:57:11Z
dc.date.issued2016
dc.identifier.citationMugruza-Vassallo, C. (2016). Different regressors for linear modelling of Electroencephalographic recordings in visual and auditory tasks. En Wearable and Implantable Body Sensor Networks (BSN). San Francisco, California 14-17 de junio 2016. doi:10.1109/BSN.2016.7516270es_ES
dc.identifier.urihttp://repositorio.ulima.edu.pe/handle/ulima/4578
dc.descriptionPublicación producto de la participación del autor en el evento 13th International Conference on Wearable and Implantable Body Sensor Networks (BSN), realizado del 14 al 17 de junio de 2016 en la ciudad de San Francisco (California, Estados Unidos).
dc.description.abstractThe use of hierarchical linear modelling has been increasing in the last 5 years to analyze EEG data. Until now, no clear comparison on linear modelling in different modalities has been done. Therefore, specific differences observed in both visual and auditory paradigms were computed with linear modelling. The Coefficient of Determination through the explained variance (R2) in Linear Modelling was sought in visual and auditory modalities. ERP scalp series of time from 100 to 300 ms for the visual task and around 150 ms to 400 for the auditory task were also plotted. Although these paradigms use different regressors, both paradigms showed reliable R2 signatures across the participants and reliable ERP scalp maps. Results accounted for different magnitudes in greater R2 values for visual modality. Auditory R2 results appeared with a reliable linear modelling when compared with R2 studies in other subjects.es_ES
dc.description.uriIndexado en Scopus
dc.description.uriAcceso restringido a la comunidad Ulima (Para acceder al texto completo si es Docente Ulima, anteponer ULIMA/ a su usuario)
dc.formatapplication/pdf
dc.language.isoenges_ES
dc.publisherIEEEes_ES
dc.relation.urihttp://downloads.ulima.edu.pe/rree_alumnos/Ponencias/PONEN4.pdf
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.sourceUniversidad de Lima
dc.sourceRepositorio Institucional - Ulima
dc.subjectIngeniería Eléctrica y Electrónica
dc.subjectElectroencefalografía
dc.subjectModelos cerebrales
dc.subjectElectrical and Electronic Engineering
dc.subjectElectroencephalography
dc.subjectBrain Models
dc.subject.classificationIngenierías / Ingeniería electrónica
dc.titleDifferent regressors for linear modelling of Electroencephalographic recordings in visual and auditory taskses_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_PE
dc.type.otherArtículo de conferencia en Scopuses_PE
dc.publisher.countryEstados Unidos
dc.description.peer-reviewRevisión por pares


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