A real time approach for QRS detection of ECG signal using network intrusion detection technique

The QRS complex is the most striking waveform within the electrocardiogram (ECG). QRS detection provides the fundamentals for almost all automated ECG analysis algorithms. We proposed a novel method for detection of QRS complexes in ECG signals using Network Intrusion Detection technique used for detection of worm in networking applications for finding the frequently repeated strings in a packet stream. A novel real-time QRS detection technique using two-phase hashing is proposed in this paper. Our technique relies more on the data stream corresponding to ECG beats than any particular feature. We use the concept of shared counters to minimize the memory requirement while efficiently shifting through suspicious strings. The algorithm automatically adjusts parameters periodically to adapt to ECG changes as QRS morphology and heart rate. The proposed algorithm correctly detects QRS complexes with negligible false positive and negative detection.