Application of HHT Algorithm to ECG QRS Detection

Electrocardiogram (ECG) signals are the most important tool in the diagnosis of cardiovascular diseases, and the QRS complexes are the most significant waveforms within ECG signals, representing the critical steps of the heart's pumping function. This study integrates the Hilbert-Huang Transform (HHT) into conventional ECG detection algorithms, which improves the real-time detection method of QRS complexes based on traditional differential thresh-old techniques. The effectiveness of the proposed method is validated using simulation results from the MIT-BIH ECG dataset provided by the Massachusetts Institute of Technology. The results indicate that the QRS complexes detection rate of the HHT-based ECG monitoring algorithm is significantly higher than that of traditional methods, thereby confirming the superiority of this approach.