Myocardial Infarction (MI) is a critical heart abnormality causing millions of fatalities worldwide every year. MI progress in three stages based on its severity causing several changes in an Electrocardiogram (ECG) signal. It is very critical to capture these variations, which requires continuous monitoring of the ECG signal of the patient. Therefore, it becomes imperative to develop a low power VLSI architecture to address the prognosis of MI. In this brief, for the first time, an area and power efficient design of a five stage classifier is proposed, which detects the progression of various stages of MI using ECG beats in real time. The proposed architecture has an area and total power utilization of 1.38mm2 and 5.12μW , respectively at SCL 180nm Bulk CMOS technology. The low power and area requirements and multiclass classification capability of the proposed design make it suitable to be used in wearable devices.
Software Implementation:
Modelsim
Xilinx
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MInSC: A VLSI Architecture for Myocardial Infarction Stages Classifier for Wearable Healthcare Applications
