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.
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Data di pubblicazione: | 2016 | |
Titolo: | Hardware-Algorithms Co-Design and Implementation of an Analog-to-Information Converter for Biosignals Based on Compressed Sensing | |
Autori: | Pareschi, Fabio; Albertini, Pierluigi; Frattini, Giovanni; Mangia, Mauro; Rovatti, Riccardo; Setti, Gianluca | |
Rivista: | IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS | |
Parole Chiave: | Analog-to-information converter (AIC); biomedical signals; compressed sensing; rakeness; smart saturation checking; Electrical and Electronic Engineering; Biomedical Engineering | |
Abstract in inglese: | 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. | |
Digital Object Identifier (DOI): | 10.1109/TBCAS.2015.2444276 | |
Handle: | http://hdl.handle.net/11392/2352101 | |
Appare nelle tipologie: | 03.1 Articolo su rivista |