QRS complex detection based on simple robust 2-D pictorial-geometrical feature

Abstract

In this paper a heuristic method aimed for detecting of QRS complexes without any pre-process<br><br>was developed. All the methods developed in previous studies were used pre-process, the most novelty of this study was suggesting a simple method which did not need any pre-process. Toward this objective, a new simple 2-D geometrical feature space was extracted from the original electrocardiogram (ECG) signal. In this method, a sliding window was moved sample-by-sample on the pre-processed ECG signal. During each forward slide of the analysis window an artificial image was generated from the excerpted segment allocated in the window. Then, a geometrical feature extraction technique based on curve-length and angle of highest point was applied to each image for establishment of an appropriate feature space. Afterwards the K-Nearest Neighbors (KNN), Artificial Neural Network (ANN) and Adaptive<br><br>Network Fuzzy Inference Systems (ANFIS) were designed and implemented to the ECG signal.<br><br>The proposed methods were applied to DAY general hospital high resolution holter data.<br><br>For detection of QRS complex the average values of sensitivity Se¼99.93% and positive predictivity Pþ¼99.92% were obtained.