A mixed-signal front-end ASIC for EEG acquisition system

Author

Haiyan Zhou ; Voelker, Matthias ; Hauer, Johann

Author_Institution

Fraunhofer IIS, Erlangen, Germany

fYear

2012

fDate

9-12 Dec. 2012

Firstpage

649

Lastpage

652

Abstract

A mixed-signal front-end ASIC for an Electroencephalogram (EEG) acquisition system is presented. It will be attached to the scalp by electrodes and detects the electrical signals from the brain, amplifies them, and converts the signals into digital data. 8 EEG channels are integrated. In each channel the EEG signals are amplified by a pre-amplifier with a gain between 10 and 1000. Following the pre-amplifier a two-stage low pass filter is applied with a selectable band of 80 Hz or 800 Hz. The whole channel has input referred noise of 2.2 μV for a signal bandwidth of 1 Hz-1 kHz. The analog to digital converter (ADC) is based on successive approximation algorithm with a resolution of 12 bit. The analog part for the ASIC consumes 3.5 mW from 1.8 V supply and occupies 4.08 mm² in 180 nm CMOS technology.

Keywords

application specific integrated circuits; bioelectric potentials; electrodes; electroencephalography; low-pass filters; medical signal detection; neurophysiology; ADC; CMOS technology; EEG acquisition system; EEG channels; EEG signals; algorithm approximation; analog to digital converter; bandwidth 1 Hz to 1 kHz; bandwidth 80 Hz; bandwidth 800 Hz; brain; digital data; electrical signal detection; electrodes; electroencephalogram acquisition system; mixed-signal front-end ASIC; power 3.5 mW; pre-amplifier; scalp; signal bandwidth; two-stage low pass filter; voltage 1.8 V; Application specific integrated circuits; Electroencephalography; IP networks; Photonic band gap; Signal resolution; EEG acquisition; SAR ADC; low input referred noise; multi channel; pre-amplifier with offset compensation;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronics, Circuits and Systems (ICECS), 2012 19th IEEE International Conference on

Conference_Location

Seville

Print_ISBN

978-1-4673-1261-5

Electronic_ISBN

978-1-4673-1259-2

Type

conf

DOI

10.1109/ICECS.2012.6463642

Filename

6463642