Paper Title
An Embedded System Approach for Early Detection of Silent Myocardial Ischemia

Abstract
Myocardial ischemia, characterized by reduced blood flow to the heart muscle, is a critical precursor to myocardial infarction. Early detection is essential to prevent severe outcomes like arrhythmias or sudden death. This paper presents an IoT-based system for real-time myocardial ischemia detection using the ARM7 LPC2148 microcontroller and Analog-to-Digital Converters (ADCs). The system acquires ECG signals via a three-electrode setup, processes them to detect ST-segment shifts and T-wave changes. Keywords - Myocardial Ischemia, Silent Myocardial Ischemia (SMI), ECG, Embedded System, IoT, ARM7 LPC2148, ADCs, ST-segment shifts, T-wave changes, AD8232, Real-time detection, Digital Signal Processing, Pan-Tompkins algorithm, QRS complex, Baseline wander, Butterworth filter, Moving average filter, Proteus simulation, MIT-BIH Arrhythmia Database, LED indicators.