IoT Based ECG to Grayscale Representation for the Prediction of Artery Deposition

The study and design entitled “IoT based ECG Grayscale representation for the prediction of Artery Deposition” was designed in response to the recent sharp rise in the number of different heart abnormalities affecting both older and younger people. The Internet of Things (IoT) age is far more beneficial for a variety of applications. The purpose of this study is to make it easier to get the ECGs of the patients, to continually monitor them, and to identify any patient problems. The Internet of Things (IoT) components needed to get a person’s ECG include an Arduino UNO microcontroller, an AD8232 ECG Sensor, and ECG Electrodes. There are three phases to this work. Using IoT devices, we physically collect an ECG signal from a person in the first phase. We are removing the noisy data from the ECG we acquired in the second step. Additionally, we divided the ECG’s 12 leads into segments, which were then represented as a grayscale image. To determine if the ECG is normal or abnormal, we analyze the data from the previous phase in the final phase.