An IoT Based Heart Healthcare Platform for the Sultanate of Oman

Abstract

The evolution of the Internet of Things (IoT) has been from the convergence of different forms of digital technologies such as embedded systems, real-time analytics, wireless communication, and sensors. The rise of cardiovascular disease (CVD) among adults in Oman has become a growing concern. All IoT-driven healthcare and wellness systems facilitate a continuous form of monitoring of several chronic conditions. The use of IoT healthcare platforms has a huge positive impact in providing timely help and improvement in general well-being. An abnormal situation caused due to irregular heartbeat rate is called arrhythmia and this may become dangerous as the cardiac system is affected due to aging and other pathological and sociological factors. In order to diagnose this abnormality, electrical impulses produced by the heart are recorded by equipment called Electrocardiogram (ECG). A wearable ECG device is used to monitor the patients heartbeats through the IoT platform. The ECG signals to arrhythmia classes are classified using Convolutional Neural Networks (CNN). 1D CNN techniques is used in state-of-the-art modern research, in order to classify this signal. Tabu Search (TS) algorithm with CNN, is used in this work to classify ECG signal image. The evaluation of the technique is done based on performance evaluation matrices which can produce enhanced outcomes, when compared to the present literature.