Myocardial infarction (MI) is a cardiac abnormality in which the coronary artery gets blocked, causing millions of fatalities every year. MI has a very high mortality and disability rate; therefore, with the detection of MI, it is also imperative to determine the location of the blockage to provide on−time treatment to avoid any fatality. In this brief, for the first time, a VLSI architecture is proposed that can determine the location of the infarction in real-time. The proposed architecture classifies the electrocardiogram (ECG) into twelve classes and achieves an average accuracy, sensitivity, and specificity of 99.90%, 99.49%, and 99.94%, respectively. Its area utilization is 1.69 mm2 at SCL 180 nm Bulk CMOS technology node, and the power consumption is 268.9 μW at 250 KHz. The low area and power requirements and real-time classification capability make the classifier suitable for wearable devices.