Detection of Atrial Fibrillation Using Artifical Neural Network with Power Spectrum Density of RR Interval of Electrocardiogram

International Conference on Science and Applied Science (Engineering and Educational Science) 2016

物理学;工业技术;教育

Afdala, Adfal^1 ; Nuryani, Nuryani^1 ; Nugroho, Anto Satrio^1

Physics Department, Post Graduate Program, Sebelas Maret University, Jl. Ir. Sutami 36A, Kentingan Jebres Surakarta

57126, Indonesia^1

关键词: Artifical neural networks;    Atrial fibrillation;    Data input;    Detection system;    Hidden layers;    Parameter learning;    Power spectrum density;    RR intervals;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/795/1/012073/pdf
DOI  :  10.1088/1742-6596/795/1/012073

来源: IOP

【 摘 要 】

Atrial fibrillation (AF) is a disorder of the heart with fairly high mortality in adults. AF is a common heart arrythmia which is characterized by a missing or irregular contraction of atria. Therefore, finding a method to detect atrial fibrillation is necessary. In this article a system to detect atrial fibrillation has been proposed. Detection system utilized backpropagation artifical neural network. Data input in this method includes power spectrum density of R-peaks interval of electrocardiogram which is selected by wrapping method. This research uses parameter learning rate, momentum, epoch and hidden layer. System produces good performance with accuracy, sensitivity, and specificity of 83.55%, 86.72 % and 81.47 %, respectively.