A 1μW 85nV/√Hz pseudo open-loop preamplifier with programmable band-pass filter for neural interface system

Sun Il Chang, Euisik Yoon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

We report an energy efficient pseudo open-loop amplifier with programmable band-pass filter developed for neural interface systems. The proposed amplifier consumes 400nA at 2.5V power supply. The measured thermal noise level is 85nV/√Hz and input-referred noise is 1.69 μ Vrms from 0.3Hz to 1 kHz. The amplifier has a noise efficiency factor of 2.43, the lowest in the differential topologies reported up to date to our knowledge. By programming the switched-capacitor frequency and bias current, we could control the bandwidth of the preamplifier from 138 mHz to 2.2 kHz to meet various application requirements. The entire preamplifier including band-pass filters has been realized in a small area of 0.043mm2 using a 0.25μm CMOS technology.

Original languageEnglish
Title of host publicationProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationEngineering the Future of Biomedicine, EMBC 2009
Pages1631-1634
Number of pages4
DOIs
Publication statusPublished - 2009
Event31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 - Minneapolis, MN, United States
Duration: 2009 Sept 22009 Sept 6

Publication series

NameProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009

Conference

Conference31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
Country/TerritoryUnited States
CityMinneapolis, MN
Period09/9/209/9/6

All Science Journal Classification (ASJC) codes

  • Cell Biology
  • Developmental Biology
  • Biomedical Engineering
  • Medicine(all)
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Health Informatics

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