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

Due to the fast growing of population, the need for providing patient care while they are at home at anytime is important and the era of homecare get the attention. 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. The most important challenge in homecare system is the accuracy because those systems are dealing with human health which is sensitive and need high accuracy. The trusted homecare system by health experts should be able to detect abnormalities and make decisions in an accurate way. To overcome the accuracy challenge, this paper presents a Cardiac Arrhythmia monitoring framework. Cardiac Arrhythmia happen when the Electrocardiogram (ECG) signal contains irregularity in their features. The raw ECG Signal is passed through signal processing stage for denoising. Then the denoised 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 improve the accuracy. Experiment results show that the proposed model is more accurate in the classification of Cardiac Arrhythmia and more reliant from caregivers point of view in comparison with other researches.