ECG-Based Personal Identification Using Empirical Mode Decomposition and Hilbert Transform View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-03

AUTHORS

R. Boostani, M. Sabeti, S. Omranian, S. Kouchaki

ABSTRACT

It is evident that biological signals of each subject (e.g., electrocardiogram signal) carry his/her unique signature; consequently, several attempts have been made to extract subject-dependent features from these signals with application to human verification. Despite numerous efforts to characterize electrocardiogram (ECG) signals and provide promising results for low population of subjects, the performance of state-of-the-art methods mostly fail in the presence of noise or arrhythmia. This paper presented an efficient and fast-to-compute ECG feature by applying empirical mode decomposition (EMD) to ECG signals, and then, instantaneous frequency, instantaneous phase, amplitude, and entropy features were extracted from the analytical form of the last EMD component. Finally, the k-nearest neighbor (kNN) classifier was utilized to classify the individuals’ features. The proposed method was compared to the conventional features such as fiducial points, correlation, wavelet coefficients, and principal component analysis (PCA). These methods were all applied to ECG signals of 34 healthy subjects derived from the Physikalisch-Technische Bundesanstalt (PTB) database. The results implied the effectiveness of the proposed method, providing 95% verification accuracy, which was not the best among the competitors but provided much lower dimensional feature space compared to the top-rank counterparts. More... »

PAGES

1-9

References to SciGraph publications

  • 2014-12. An algorithm for fast Hilbert transform of real functions in ADVANCES IN COMPUTATIONAL MATHEMATICS
  • 2017-03. An Online Subspace Denoising Algorithm for Maternal ECG Removal from Fetal ECG Signals in IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY, TRANSACTIONS OF ELECTRICAL ENGINEERING
  • 2014-12. A novel low-complexity post-processing algorithm for precise QRS localization in SPRINGERPLUS
  • 2015-12. Individual identification via electrocardiogram analysis in BIOMEDICAL ENGINEERING ONLINE
  • 2008. ISAR Imaging of Rotating Target with Equal Changing Acceleration Based on the Cubic Phase Function in APPLIED SIGNAL PROCESSING
  • 2007-12. Principal Component Analysis in ECG Signal Processing in APPLIED SIGNAL PROCESSING
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    http://scigraph.springernature.com/pub.10.1007/s40998-018-0055-7

    DOI

    http://dx.doi.org/10.1007/s40998-018-0055-7

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