Simulative Wearable Sensor Modelling in Remote Electrocardiogram Monitoring

The purpose of this paper is to perform in-depth research on the latest technology of smart medical evaluation tools for ECG signal analysis, which is applied in remote monitoring systems for patients suffering from chronic heart diseases. This system accomplishes its function by processing ECG signal sets, enabling it to classify ECG segments as normal or abnormal. This is critical for remote patient management. To ensure the accuracy of the classification of ECG segments, the system is provided with sixteen different features, each of which carries a significant number of data points. Specifically, each of these sixteen features is calculated from a 140-point ECG segment.