کنفرانس مهندسی برق ایران

صفحه اصلی / سی و دومین کنفرانس بین المللی مهندسی برق

An active learning approach for classification of several arrhythmias in ECG signal

نویسندگان :

Nastaran Darbani¹ Danial Katoozian² Hossein Hosseini-Nejad³

1- دانشگاه صنعتی خواجه نصیرالدین طوسی 2- دانشگاه صنعتی خواجه نصیرالدین طوسی 3- دانشگاه صنعتی خواجه نصیرالدین طوسی

کلمات کلیدی :

Active learning،Electrocardiography،Arrhythmia،Stochastic Gradient Descent،Medical Assistant،Machine learning

چکیده :

Abstract—Electrocardiography (ECG) is a widely used method for analyzing the condition of the heart. Due to the significant number of ECG signals that require analysis on a daily basis, the implementation of a machine learning algorithm as a medical assistant to automatically analyze these signals has become crucial. While several algorithms have been proposed for this purpose, most of them are limited to initial training and datasets. However, as a medical assistant system, new labeled signals provided by experts are available daily, which can be utilized to enhance accuracy and improve overall performance. Therefore, this paper introduces an active learning approach to address this issue. The proposed approach is evaluated using real data from multiple individuals and various scenarios to demonstrate its practicality and superior accuracy compared to traditional methods.