A New Approach to Compressing ECG Signals with Trained Overcomplete Dictionary

SEUNGJAE LEE; Jun Luan; Pai Chou

4th International Conference on Wireless Mobile Communication and Healthcare - "Transforming healthcare through innovations in mobile and wireless technologies"

Research Article

A New Approach to Compressing ECG Signals with Trained Overcomplete Dictionary

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Cite: BibTeX Plain Text

@INPROCEEDINGS{10.4108/icst.mobihealth.2014.257383,
    author={SEUNGJAE LEE and Jun Luan and Pai Chou},
    title={A New Approach to Compressing ECG Signals with Trained Overcomplete Dictionary},
    proceedings={4th International Conference on Wireless Mobile Communication and Healthcare - "Transforming healthcare through innovations in mobile and wireless technologies"},
    publisher={IEEE},
    proceedings_a={MOBIHEALTH},
    year={2014},
    month={12},
    keywords={k-svd ecg compression overcomplete dictionary},
    doi={10.4108/icst.mobihealth.2014.257383}
}

SEUNGJAE LEE
Jun Luan
Pai Chou
Year: 2014
A New Approach to Compressing ECG Signals with Trained Overcomplete Dictionary
MOBIHEALTH
IEEE
DOI: 10.4108/icst.mobihealth.2014.257383

SEUNGJAE LEE^,*, Jun Luan¹, Pai Chou¹

1: University of California Irvine

*Contact email: leesj3@uci.edu

Abstract

We propose a new ECG data compression algorithm based on a learned overcomplete dictionary to exploit the correlation between signals in adjacent heart beats. The learned overcomplete dictionary is constructed by K-SVD dictionary learning algorithm, after preprocessing and normalization of length and magnitude. Using the overcomplete dictionary, the proposed algorithm can find sparse estimation, which can repre- sent the ECG signal effectively. Experimental results on MIT-BIH arrhythmia database confirms that our proposed algorithm has high compression ratio while minimizing data distortion.

Keywords: k-svd ecg compression overcomplete dictionary

Published: 2014-12-05
Publisher: IEEE

: http://dx.doi.org/10.4108/icst.mobihealth.2014.257383