Hardware-Algorithms Co-Design and Implementation of an Analog-to-Information Converter for Biosignals Based on Compressed Sensing

Fabio Pareschi, Pierluigi Albertini, Giovanni Frattini, Mauro Mangia, Riccardo Rovatti, Gianluca Setti

Research output: Contribution to journalArticlepeer-review

88 Scopus citations

Abstract

We report the design and implementation of an Analog-to-Information Converter (AIC) based on Compressed Sensing (CS). The system is realized in a CMOS 180 nm technology and targets the acquisition of bio-signals with Nyquist frequency up to 100 kHz. To maximize performance and reduce hardware complexity, we co-design hardware together with acquisition and reconstruction algorithms. The resulting AIC outperforms previously proposed solutions mainly thanks to two key features. First, we adopt a novel method to deal with saturations in the computation of CS measurements. This allows no loss in performance even when 60% of measurements saturate. Second, the system is able to adapt itself to the energy distribution of the input by exploiting the so-called rakeness to maximize the amount of information contained in the measurements.
Original languageEnglish (US)
Pages (from-to)149-162
Number of pages14
JournalIEEE Transactions on Biomedical Circuits and Systems
Volume10
Issue number1
DOIs
StatePublished - Feb 1 2016
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-02-15

ASJC Scopus subject areas

  • Biomedical Engineering
  • Electrical and Electronic Engineering

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