FRACTIONAL FOURIER TRANSFORM BASED QRS COMPLEX DETECTION IN ECG SIGNAL

By exploiting fractional-Fourier-transform (FrFT), a novel technique for the QRS complex detection is proposed. The application of the FrFT rotates the Electrocardiograph (ECG) signal in the time-frequency plane. We claim this rotation can give simple and effective QRS complex detection even in the presence of versatile artifacts, such as left-bundle-branch-block, right-bundle-branch-block, and negative polarization. In this work, in the first step, the noise and baseline drifts are removed by applying a wavelet transform on the given ECG signal. While, in the next step, the clean ECG signal is passed through the proposed algorithm, which rotates the ECG signal in the time-frequency plane and detects the QRS complex very easily. The proposed algorithm validated over the 48 signals of the MIT-BIH arrhythmia database, and it yielded 26 false-positive and only five false-negatives compared to the 80 and 42, the best result reported so far.