This paper proposes an algorithm using
Empirical Mode Decomposition (EMD) and k-means for
the detection of QRS complexes present in the ECG
signal. EMD is an innovative method for decomposing
any time varying, nonlinear and non-stationerysignal
into a set of intrinsic mode functions (IMF). This
automated algorithm is applied to the filtered ECG
signal for its decomposition into its intrinsic components
and further its classification is done using k-means
classifier. Dataset-3 of the CSE multi-lead measurement
library is used for validating the performance of the
algorithm. Detection rate of the proposed algorithm
came out to be 99.42% with sensitivity (Se) and
prediction (+P) rates being 99.39% and 99.93%
respectively. The performance of this algorithm is quite
satisfactory amongst many algorithms used for the
automated detection of QRS complexes
Keywords : Empirical Mode decomposition, K-means, ECG signal, QRS complex