A Real-Time QRS Complex Detector Based On Discrete Wavelet Transform And Adaptive Threshold As Standalone Application On ARM Microcontrollers

The electrocardiogram (ECG) is one of the most used tools to detect the health state of the heart. The QRS complex is an important waveform in an ECG signal and it serves as reference point for most ECG signal processing algorithms. In this paper a real-time QRS complex detector based on discrete wavelet transform (DWT) is proposed. In contrast with other algorithms, ours is able to automatically select the detail coefficients that will be used to detect the QRS complex after applying the DWT to the signal. The algorithm was compared with other published methods and evaluated with two datasets, one of them with arrhythmia and the other in healthy conditions. The results for the signals with arrhythmia were 99.30% for sensitivity, 99.61% for positive predictivity and 1.12% for error detection rate, while in the signals in healthy conditions the values were of 99.95%, 99.98% and 0.0006% respectively. Finally, the algorithm was implemented on an ARM microcontroller showing its real-time processing capability