A 64-channel inductively-powered neural recording sensor array

Author

Rodriguez-Perez, Alberto ; Masuch, J. ; Rodriguez-Rodriguez, Jose A. ; Delgado-Restituto, Manuel ; Rodriguez-Vazquez, Angel

Author_Institution

Inst. of Microelectron. of Sevilla, Univ. of Sevilla, Sevilla, Spain

fYear

2012

fDate

28-30 Nov. 2012

Firstpage

228

Lastpage

231

Abstract

This paper reports a 64-channel inductively powered neural recording sensor array. Neural signals are acquired, filtered, digitized and compressed in the channels. Additionally, each channel implements a local auto-calibration mechanism which configures the transfer characteristics of the recording site. The system has two operation 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 transmitted. Data streams coming from the channels are serialized by an embedded digital processor and transferred to the outside by means of the same inductive link used for powering the system. Simulation results show that the power consumption of the complete system is 377μW.

Keywords

bioelectric phenomena; biomedical electronics; calibration; data acquisition; data compression; feature extraction; filtering theory; medical signal processing; neurophysiology; sensor arrays; 64-channel inductively-powered neural recording sensor array; data streams; embedded digital processor; feature vector extraction; information capturing; local autocalibration mechanism; neural signal acquisition; neural signal compression; neural signal digitalisation; neural signal filtering; neural spikes detection; power 377 muW; power consumption; transfer characteristics; uncompressed raw data; Arrays; Calibration; Clocks; Electronics packaging; Feature extraction; Power demand;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Circuits and Systems Conference (BioCAS), 2012 IEEE

Conference_Location

Hsinchu

Print_ISBN

978-1-4673-2291-1

Electronic_ISBN

978-1-4673-2292-8

Type

conf

DOI

10.1109/BioCAS.2012.6418455

Filename

6418455