Detecting QRS Complex in ECG using Wavelets and Cubic Spline Interpolation

Luiz C. Rodrigues and MaurĂ­cio Marengoni


biomedical signal processing, health care information systems, ECG


Due to its easy application and low cost, the eletrocardiogram (ECG) is a resource with large application in the heart health assessment and, among all the ECG components, the QRS Complex is the most significant fiducial point. A fundamental step in any study of digital signal processing of ECG, as well heart beats classification, is the QRS complex detection. Several works on QRS detection are available in the literature, however the robustness and high level of precision is still a matter of studies. In this work we present a QRS detector relying in Daubechies wavelets transform and cubic spline interpolation. Using waveletes transform, the ECG is first pre-processed for noise removal and baseline wandering and then, combining wavelets and cubic spline interpolation, the QRS complex is enhanced and other noise components are attenuated. This signal is submitted to a peak detector module whose purpose is to identify the R wave. For development and validation of this work we used the Massachusetts Institute of Technology-Beth Israel Hospital(MIT-BIH) Arrithmias database. The final result showed a sensitivity level above 96.5% in most of the tested records, this results are presented at the end of this work.

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