A 330μW, 64-channel neural recording sensor with embedded spike feature extraction and auto-calibration

Rodríguez Pérez, Alberto; Delgado Restituto, Manuel; Darie, Ángela; Soto Sánchez, Cristina; Fernández Jover, Eduardo; Rodríguez Vázquez, Ángel Benito

doi:http://dx.doi.org/10.1109/ASSCC.2014.7008896

Ponencia

dc.creator	Rodríguez Pérez, Alberto
dc.creator	Delgado Restituto, Manuel
dc.creator	Darie, Ángela
dc.creator	Soto Sánchez, Cristina
dc.creator	Fernández Jover, Eduardo
dc.creator	Rodríguez Vázquez, Ángel Benito
dc.date.accessioned	2016-02-01T07:49:51Z
dc.date.available	2016-02-01T07:49:51Z
dc.date.issued	2014
dc.identifier.isbn	978-1-4799-4090-5	es
dc.identifier.uri	http://hdl.handle.net/11441/33648
dc.description	http://digital.csic.es/handle/10261/111553	es
dc.description.abstract	his paper reports an integrated 64-channel neural recording sensor. Neural signals are acquired, filtered, digitized and compressed in the channels. Additionally, each channel implements an auto-calibration mechanism which configures the transfer characteristics of the recording site. The system has two transmission modes; in one case the information captured by the channels is sent as uncompressed raw data; in the other, feature vectors extracted from the detected neural spikes are released. Data streams coming from the channels are serialized by an embedded digital processor. Experimental results, including in vivo measurements, show that the power consumption of the complete system is lower than 330μW.	es
dc.format	application/pdf	es
dc.language.iso	eng	es
dc.publisher	Institute of Electrical and Electronics Engineers	es
dc.relation.ispartof	IEEE 2014 Asian Solid-State Circuits Conference: 205-208	es
dc.rights	Attribution-NonCommercial-NoDerivatives 4.0 Internacional	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	*
dc.title	A 330μW, 64-channel neural recording sensor with embedded spike feature extraction and auto-calibration	es
dc.type	info:eu-repo/semantics/conferenceObject	es
dcterms.identifier	https://ror.org/03yxnpp24
dc.type.version	info:eu-repo/semantics/publishedVersion	es
dc.rights.accessRights	info:eu-repo/semantics/openAccess	es
dc.contributor.affiliation	Universidad de Sevilla. Departamento de Electrónica y Electromagnetismo	es
dc.relation.publisherversion	http://dx.doi.org/10.1109/ASSCC.2014.7008896	es
dc.identifier.doi	http://dx.doi.org/10.1109/ASSCC.2014.7008896	es
dc.identifier.idus	https://idus.us.es/xmlui/handle/11441/33648

Ficheros	Tamaño	Formato	Ver	Descripción
A 330µW, 64-Channel Neural ...	2.030Mb	[PDF]	Ver/Abrir

Este registro aparece en las siguientes colecciones

Ponencias (Electrónica y Electromagnetismo)

Mostrar el registro sencillo del ítem

Excepto si se señala otra cosa, la licencia del ítem se describe como: Attribution-NonCommercial-NoDerivatives 4.0 Internacional