NDLI: On projection matrices and dictionaries in ECG compressive sensing

Content Provider	IEEE Xplore Digital Library
Author	Fira, M. Goras, L.
Copyright Year	2014
Description	Author affiliation: Fac. of Electron. & Telecommun., Gh. Asachi Tech. Univ., Iasi, Romania (Goras, L.) \|\| Inst. for Comput. Sci., Iasi, Romania (Fira, M.)
Abstract	In this communication we propose and discuss comparatively several techniques for ECG signal compression inspired from the fundamentals of compressed sensing (CS) theory, focusing on acquisition techniques, projection matrices and reconstruction dictionaries and on the effects of the preprocessing involved. Essentially, we investigate and discuss two approaches. The first approach for ECG signal compression relies on the direct CS acquisition of the signal with no preprocessing of the waveforms before taking the projections, neither for the construction of the dictionaries. This “genuine” CS we will call patient specific classical compressed sensing (PSCCS) since the dictionary is built from patient initial recordings. The second approach implements a specific preprocessing stage designed to enhance sparsity and improve recoverability, based on segmenting the signal into single heart beats (also known as cardiac patterns) - denoted further as cardiac patterns compressed sensing - (CPCS) since in this case the acquired signals and the dictionary atoms are preprocessed segmented cardiac beats without or with centering of the R wave.
Starting Page	3
Ending Page	8
File Size	303579
Page Count	6
File Format	PDF
ISBN	9781479958870
e-ISBN	9781479958887
DOI	10.1109/NEUREL.2014.7011444
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-11-25
Publisher Place	Serbia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Dictionaries Electrocardiography Vectors Gaussian distribution Pathology Compressed sensing Image reconstruction pursuit algorithms ECG compression electrocardiography
Content Type	Text
Resource Type	Article

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