QRS complex detection using Empirical Mode Decomposition

In this paper, we present a new Empirical Mode Decomposition based algorithm for the purpose of QRS complex detection. This algorithm requires the following stages: a high-pass filter, signal Empirical Mode Decomposition, a nonlinear transform, an integration and finally, a low-pass filter is used. In order to evaluate the proposed technique, the well known ECG MIT-BIH database has been used. Moreover it is compared to a reference technique, namely ''Christov's'' detection method. As it will be shown later, the proposed algorithm allows to achieve high detection performances, described by means both the sensitivity and the specificity parameters.

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