Atrial fibrillation detection using RR-interval irregularity supported by particle swarm optimization

Atrial Fibrillation (AF) is the most common arrhythmia. AF has increased peoples health and financial burdens. Patients with AF should be stratified according to a predictive stroke-risk score. According to the complication, risk factor and data of epidemiology, AF is always interesting to be multidisciplinary research topic, one of which is the developing algorithms for … Read more

Detecting atrial fibrillation using statistical features of electrocardiographic interbeat interval

This article presents a technique for detecting atrial fibrillation (AF). The technique employs electrocardiographic interbeat interval (IBI) alteration. The IBI is the time interval between individual beats of electrocardiogram. Two statistical, mean and standard deviation of IBI are examined. For the classification a support vector machine (SVM) with RBF function is applied. We have examined … Read more

Identification of fetal QRS with base of abdominal electrocardiogram using backpropagation artifical neural network

A method for fetal QRS identification (FECG) originating from a non-invasive recording of abdominal electrocardiogram (AECG) is conducted. The method utilizes a backpropagation Artificial Neural Network (ANN). An abdominal electrocardiogram recording is extracted to obtain an electrocardiographic QRS. The method is tested using the clinical dataset of Abdominal and Direct Fetal Electrocardiogram Database (adfecgdb) from … Read more