Low-complexity greedy algorithm in compressed sensing for the adapted decoding of ECGs

Alex Marchioni, Mauro Mangia, Fabio Pareschi, Riccardo Rovatti, Gianluca Setti

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

1 Scopus citations


The balanced weighted orthogonal matching pursuit (bWOMP) algorithm for recovering signals in compressed sensing (CS) based system is presented as a specialized recovering tool for Electrocardiograph (ECG) signals. Being based on the standard OMP approach, bWOMP is a lightweight reconstruction algorithm both in terms of complexity and memory footprint. Furthermore, the concept of weighting is introduced in the algorithm by exploring a prior knowledge on ECG signals. Experimental results show a performance increase of about 10 dB with respect to the standard OMP approach, and also an increase with respect to the decoding approaches considered as the state-of-the-art. In this case the gain could be as high as 4 dB with respect to the best of currently known decoding approaches.
Original languageEnglish (US)
Title of host publication2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages4
ISBN (Print)9781509058037
StatePublished - Mar 23 2017
Externally publishedYes

Bibliographical note

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


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