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

Identification of atrial fibrillation using descriptive statistic features and adaptive Neuro-Fuzzy inference system

Atrial fibrillation (AF) is one of the most common arrhythmia which can cause a serious problem. Nevertheless, well treated AF might not lead to any further complication. Early detection of AF could be an important preventative step that have to be conducted. In this article, we aim to make an automatic detection of atrial fibrillation. … Read more