title: Energy and Quality Evaluation for Compressive Sensing of Fetal Electrocardiogram Signals.
abstract: This manuscript addresses the problem of non-invasive fetal Electrocardiogram (ECG) signal acquisition with low power/low complexity sensors. A sensor architecture using the Compressive Sensing (CS) paradigm is compared to a standard compression scheme using wavelets in terms of energy consumption vs. reconstruction quality, and, more importantly, vs. performance of fetal heart beat detection in the reconstructed signals. We show in this paper that a CS scheme based on reconstruction with an over-complete dictionary has similar reconstruction quality to one based on wavelet compression. We also consider, as a more important figure of merit, the accuracy of fetal beat detection after reconstruction as a function of the sensor power consumption. Experimental results with an actual implementation in a commercial device show that CS allows significant reduction of energy consumption in the sensor node, and that the detection performance is comparable to that obtained from original signals for compression ratios up to about 75%.
authors.affiliation: Polytechnic Department of Engineering and Architecture, University of Udine, Via delle Scienze 206, 33100 Udine, Italy. dapoian.giulia@spes.uniud.it.
authors.forename: Giulia
authors.initials: G
authors.lastname: Da Poian
authors.affiliation: Polytechnic Department of Engineering and Architecture, University of Udine, Via delle Scienze 206, 33100 Udine, Italy. brandalise.denis@spes.uniud.it.
authors.forename: Denis
authors.initials: D
authors.lastname: Brandalise
authors.affiliation: Polytechnic Department of Engineering and Architecture, University of Udine, Via delle Scienze 206, 33100 Udine, Italy. bernardini@uniud.it.
authors.forename: Riccardo
authors.initials: R
authors.lastname: Bernardini
authors.affiliation: Polytechnic Department of Engineering and Architecture, University of Udine, Via delle Scienze 206, 33100 Udine, Italy. rinaldo@uniud.it.
authors.forename: Roberto
authors.initials: R
authors.lastname: Rinaldo
mesh_terms: D000465:Algorithms; D015374:Biosensing Techniques / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D059015:Wireless Technology
keywords: compressive sensing; fetal ECG; wearable sensors