ECG Data Processing Methods for Intelligent Remote ECG Monitoring System: A Survey

The integration of the Internet of Things (IoT), edge computing and cloud computing has facilitated the development of an advanced intelligent remote ECG monitoring system. This system offers a convenient platform for remote monitoring, consultation services and diagnosis for patients with cardiovascular conditions. However, challenges persist regarding data noise interference and limited diagnostic accuracy. Therefore, mitigating noise interference and improving diagnostic precision remain critical issues to address. In this study, we introduce an intelligent remote ECG monitoring system that consists of three main components: the user terminal (data collection device), the remote ECG monitoring center, and the analysis and diagnosis modules. The data captured by sensors from wearable devices are collected in real time by the user terminal, formatted into a standard structure and then transmitted to the remote electrocardiogram monitoring center. Within the intelligent remote ECG monitoring system, the remote ECG monitoring center performs key tasks, such as preprocessing, feature extraction and classification of ECG data. Subsequently, examining the advancements made within the realm of the intelligent remote ECG monitoring system, a comprehensive overview is presented. This encompasses the refinement process, segmentation of ECG signals and the categorization of arrhythmias. Finally, we propose potential directions for future research in ECG data processing within the context of intelligent remote ECG monitoring systems.