A Smart Health Application for Real-Time Cardiac Disease Detection and Diagnosis Using Machine Learning on ECG Data
作者：
Utsha U.T.;Hua Tsai I.;Morshed B.I.
通讯作者：
Utsha, U.T.
作者机构：
Department of Computer Science, Texas Tech University, Lubbock, United States
通讯机构：
Department of Computer Science, United States
语种：
英文
关键词：
Cardiac disease,Electrocardiograms,Pre-Trained Model,Smart-Health Application
期刊：
IFIP Advances in Information and Communication Technology
ISSN：
1868-422X
年：
2024
卷：
683 AICT
页码：
135-150
会议名称：
6th IFIP International Conference on Internet of Things, IFIP IoT 2023
会议时间：
2 November 2023 through 3 November 2023
基金类别：
This material is based upon work supported by the National Science Foundation under Grant No. 2105766. The development of the ECG device was performed by Mahfuzur Rahman, Robert Hewitt, and Bashir I. Morshed.
摘要：
Cardiac disease, also referred to as cardiovascular disease, is a collection of conditions that affect the heart and blood vessels. Medical professionals typically use a combination of medical history, physical examination, and various diagnostic tests, such as electrocardiograms (ECG/EKG), echocardiograms, and stress tests, to diagnose cardiac diseases. In response to this issue, we are introducing a mobile application that continuously monitors electrocardiogram signals and displays both average and instantaneous heart rates. The aim of this project is to detect and diagnose cardiac diseases so that patients can become informed about their heart health and take appropri...
