Design and Development of Cloud Based Real Time ECG Anomaly Detection

Abstract

The functionality of the heart is assessed by analysing the electrocardiogram (ECG) signal. Numerous methods were developed for the accurate detection of heart diseases utilising the recorded ECG signals. However, individuals with serious heart diseases must be constantly observed, especially if there are few indicating bio-signal patterns. Real-time data collection and processing enables early detection of heart diseases and prevent complications. The AD8232 sensor is used in the project along with its interface with the Node MCU for real time acquisition of ECG signal. The intervals of the PQRST wave are thoroughly investigated utilizing a novel windowing approach based on Wavelet Transform. To increase the QoS in the healthcare system, the final findings are displayed on both the system and the cloud interface. In this work, we compared the ECG parameters with those from well-known smartwatches. The outcomes demonstrated a striking match between the ECG parameters acquired using our method and those obtained using smartwatches. This verifies the precision and dependability of our system in monitoring the ECG parameters from ECG signal. Our methodology has the potential to be a dependable and practical solution for heart rate monitoring in real-time and distant healthcare applications because our algorithm and smartwatches consistently report heart rate rates in the same range.