Discrete Wavelet Transform Based Algorithm for Recognition of QRS Complexes
This work addresses ECG signal analysis for medical diagnostics, but it is incremental as it applies an existing method to a specific task.
The paper tackled the problem of detecting QRS complexes in ECG signals using a Discrete Wavelet Transform-based algorithm, achieving an average detection rate of 98.1% on the MIT-BIH Arrhythmia database.
This paper proposes the application of Discrete Wavelet Transform (DWT) to detect the QRS (ECG is characterized by a recurrent wave sequence of P, QRS and T-wave) of an electrocardiogram (ECG) signal. Wavelet Transform provides localization in both time and frequency. In preprocessing stage, DWT is used to remove the baseline wander in the ECG signal. The performance of the algorithm of QRS detection is evaluated against the standard MIT BIH (Massachusetts Institute of Technology, Beth Israel Hospital) Arrhythmia database. The average QRS complexes detection rate of 98.1 % is achieved.