An Internet of Things (IoT) Homecare Management System Using Cardiac Arrhythmia Classification

Almazroa, Areej; Sun, Hongjian

Abstract

Due to the fast growing of population, a lot of hospitals get crawdad from the huge amount of patients visits. The need for providing patient care while they are at home at anytime is important and the era of homecare should started. Internet of Things (IoT) is widely known and used by different fields. IoT with the assist of homecare will help in reducing the burden upon hospitals. IoT with homecare bring up several benefits such as minimizing human exertions, economical advantages and raising in efficiency and effectiveness. The most important feature in homecare system is the accuracy because those systems are dealing with human health which is sensitive and need high amount of accuracy. The trusted homecare system by health experts should be able to detect abnormalities and make decisions in an accurate way that reaches 100%. To overcome the accuracy limitation, this paper presents a Cardiac Arrhythmia monitoring framework. Cardiac Arrhythmia happend when the Electrocardiogram (ECG) signal contains irregularity in their features. The raw ECG Signal is passed through signal processing stage to clear it from noise. Then the cleared signal is passed through the feature extraction stage to extract a number of features that are used in the classification stage. After that, a classification stage to detect Cardiac Arrhythmia is made using deep learning to raise the accuracy. Based on experiment results, the proposed model is more accurate in the classification of Cardiac Arrhythmia and more reliant from caregivers point of view in comparing with other researches.

Citation

Almazroa, A., & Sun, H. (2021). An Internet of Things (IoT) Homecare Management System Using Cardiac Arrhythmia Classification. . https://doi.org/10.1109/ntms49979.2021.9432672

• Conference Name: 11th IFIP International Conference on New Technologies, Mobility and Security (NTMS)
• Conference Location: Paris
• Start Date: Apr 19, 2021
• End Date: Apr 21, 2021
• Online Publication Date: Mar 19, 2020
• Publication Date: 2021
• Deposit Date: Apr 28, 2021
• Publicly Available Date: Apr 28, 2021
• Publisher: Institute of Electrical and Electronics Engineers
• Pages: 1-5
• DOI: https://doi.org/10.1109/ntms49979.2021.9432672
• Additional Information: Date of Conference: 19-21 April 2021