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Title

A 330μW, 64-Channel Neural Recording Sensor with Embedded Spike Feature Extraction and Auto-calibration

AuthorsRodríguez-Pérez, Alberto ; Delgado-Restituto, Manuel ; Darie, Ángela; Soto-Sánchez, Cristina; Fernández-Jover, Eduardo; Rodríguez-Vázquez, Ángel
Issue Date2014
PublisherInstitute of Electrical and Electronics Engineers
CitationIEEE 2014 Asian Solid-State Circuits Conference: 205-208
Abstracthis 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.
Publisher version (URL)http://dx.doi.org/10.1109/ASSCC.2014.7008896
URIhttp://hdl.handle.net/10261/111553
DOI10.1109/ASSCC.2014.7008896
Appears in Collections:(IMSE-CNM) Artículos
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