Research Article
Performance Investigation of Empirical Mode Decomposition in Biomedical Signals
@INPROCEEDINGS{10.1007/978-3-642-20865-2_16, author={Alexandros Karagiannis and Philip Constantinou}, title={Performance Investigation of Empirical Mode Decomposition in Biomedical Signals}, proceedings={Wireless Mobile Communication and Healthcare. Second International ICST Conference, MobiHealth 2010, Ayia Napa, Cyprus, October 18-20, 2010. Revised Selected Papers}, proceedings_a={MOBIHEALTH}, year={2012}, month={5}, keywords={Empirical Mode Decomposition ECG Intrinsic Mode Functions extrema time of computation}, doi={10.1007/978-3-642-20865-2_16} }- Alexandros Karagiannis
Philip Constantinou
Year: 2012
Performance Investigation of Empirical Mode Decomposition in Biomedical Signals
MOBIHEALTH
Springer
DOI: 10.1007/978-3-642-20865-2_16
Abstract
In this paper, the performance of Empirical Mode Decomposition (EMD) applied in biomedical signals is investigated and especially it is considered the case of electrocardiogram (ECG). Synthetic ECG signals corrupted with White Gaussian Noise (WGN) as well as real ECG records are employed and a variety of time series lengths is processed with EMD in order to extract the Intrinsic Mode Functions (IMF). Computation time is measured upon the completion of the process in simulation campaign stage and real records stage and the results are compared in both cases. Spectral characteristics of the time series as well as the tendency to exhibit extrema are the key factors with significant impact on both computation time as well as the total number of IMFs produced.
