Wavelet Based Dictionaries for Dimensionality Reduction of ECG Signals

Research output: Contribution to journalArticle

Abstract

Dimensionality reduction of ECG signals is considered within the framework of sparse representation. The approach constructs the signal model by selecting
elementary components from a redundant dictionary via a greedy strategy.
The proposed wavelet dictionaries are built from the multiresolution scheme, but
translating the prototypes within a shorter step than that corresponding to the wavelet basis. The reduced representation of the signal is shown to be suitable for compression at low level distortion. In that regard, compression results are superior to previously reported benchmarks on the MIT-BIH Arrhythmia data set.
LanguageEnglish
JournalBiomedical Signal Processing and Control
Publication statusAccepted/In press - 7 Jun 2019

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Glossaries
Electrocardiography
Benchmarking
Cardiac Arrhythmias
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Cite this

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title = "Wavelet Based Dictionaries for Dimensionality Reduction of ECG Signals",
abstract = "Dimensionality reduction of ECG signals is considered within the framework of sparse representation. The approach constructs the signal model by selectingelementary components from a redundant dictionary via a greedy strategy.The proposed wavelet dictionaries are built from the multiresolution scheme, but translating the prototypes within a shorter step than that corresponding to the wavelet basis. The reduced representation of the signal is shown to be suitable for compression at low level distortion. In that regard, compression results are superior to previously reported benchmarks on the MIT-BIH Arrhythmia data set.",
author = "Laura Rebollo-Neira and Dana Cerna",
year = "2019",
month = "6",
day = "7",
language = "English",
journal = "Biomedical Signal Processing and Control",
issn = "1746-8094",
publisher = "Elsevier",

}

Wavelet Based Dictionaries for Dimensionality Reduction of ECG Signals. / Rebollo-Neira, Laura ; Cerna, Dana .

In: Biomedical Signal Processing and Control, 07.06.2019.

Research output: Contribution to journalArticle

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AB - Dimensionality reduction of ECG signals is considered within the framework of sparse representation. The approach constructs the signal model by selectingelementary components from a redundant dictionary via a greedy strategy.The proposed wavelet dictionaries are built from the multiresolution scheme, but translating the prototypes within a shorter step than that corresponding to the wavelet basis. The reduced representation of the signal is shown to be suitable for compression at low level distortion. In that regard, compression results are superior to previously reported benchmarks on the MIT-BIH Arrhythmia data set.

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