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On ECG Compressed Sensing using Specific Overcomplete DictionariesFIRA, M. , GORAS, L. , BARABASA, C. , CLEJU, N.
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compressed sensing, biomedical signal processing, electrocardiography, pursuit algorithms, signal processing algorithms
signal(12), wavelet(6), sensing(6), processing(6), biomed(6), tbme(5), signals(5), sampling(5), classification(5), science(4)
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About this article
Date of Publication: 2010-11-30
Volume 10, Issue 4, Year 2010, On page(s): 23 - 28
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2010.04004
Web of Science Accession Number: 000284782700004
SCOPUS ID: 78649711600
The paper presents a number of results regarding the construction of specific overcomplete dictionaries for ECG compressed sensing (CS). The dictionaries were built using normal and patological cardiac patterns extracted from 24 recordings of the MIT-BIH Arrhythmia Database. It has been shown that the compression results obtained using the CS concept based on specific dictionaries are better that those using the wavelet overcomplete dictionaries. Starting from the concept of sparse signal with respect to a given overcomplete dictionary the paper present several results regarding the possibility of simple pattern classification as well.
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