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Different regressors for linear modelling of Electroencephalographic recordings in visual and auditory tasks

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dc.contributor.author Mugruza-Vassallo, Carlos
dc.contributor.other Mugruza-Vassallo, Carlos
dc.date.accessioned 2017-07-19T17:57:11Z
dc.date.available 2017-07-19T17:57:11Z
dc.date.issued 2016
dc.identifier.citation Mugruza-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.2016.7516270 es_ES
dc.identifier.uri http://repositorio.ulima.edu.pe/handle/ulima/4578
dc.description Publicación 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.abstract The 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.uri Indexado en Scopus
dc.description.uri Acceso restringido a la comunidad Ulima (Para acceder al texto completo si es Docente Ulima, anteponer ULIMA/ a su usuario)
dc.format application/pdf
dc.language.iso eng es_ES
dc.publisher IEEE es_ES
dc.relation.uri http://downloads.ulima.edu.pe/rree_alumnos/Ponencias/PONEN4.pdf
dc.rights info:eu-repo/semantics/restrictedAccess
dc.source Universidad de Lima
dc.source Repositorio Institucional - Ulima
dc.subject Ingeniería Eléctrica y Electrónica
dc.subject Electroencefalografía
dc.subject Modelos cerebrales
dc.subject Electrical and Electronic Engineering
dc.subject Electroencephalography
dc.subject Brain Models
dc.subject.classification Ingenierías / Ingeniería electrónica
dc.title Different regressors for linear modelling of Electroencephalographic recordings in visual and auditory tasks es_ES
dc.type info:eu-repo/semantics/conferenceObject es_PE
dc.type.other Artículo de conferencia en Scopus es_PE
dc.publisher.country Estados Unidos
dc.description.peer-review Revisión por pares


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