QRS complex detection using cuckoo search optimization algorithm

Accurate detection of QRS complexes is a prerequisite of all ECG signal processing applications. In this paper, a new adaptive filter (AF), employing cuckoo search optimization algorithm (COA), is proposed for generating feature for QRS complex detection. An efficient peak detection algorithm, coupled with search-back mechanism for detecting missed peaks, is also proposed. The combination of COA with AF and an effective peak detection algorithm with search-backs for missed peaks are the novelties presented in this paper. The performance results of proposed methodology are evaluated and compared with state-of-the-art methods. It is proved from the results that the proposed COA-AF based QRS detector gives efficient performance with sensitivity (%Se), positive predictivity (%P+), and detection error rate (%DER) of 99.75%, 99.79%, and 0.44% respectively.