• D. Divakar
• Mrs. B.Sarada

Myocardial infarction is a critical cardiac condition that poses a significant threat to human life due to the blockage of coronary arteries. Timely detection and precise localization of the infarction site are essential for effective treatment and reducing mortality rates. While wearable devices hold great promise for continuous health monitoring, existing solutions often struggle with challenges such as high-power demands, vulnerability to motion-related noise, and an inability to localize myocardial infarctions during physical activity. To address these issues, we propose an enhanced version of an SNN-inspired VLSI architecture designed for real-time myocardial infarction classification in ambulatory settings. The proposed system incorporates advanced signal preprocessing methods to eliminate motion artifacts and background noise, ensuring accurate analysis of electrocardiogram signals even during movement or in noisy environments.

SNN-inspired VLSI, Myocardial infarction, cardiac condition, motion-related noise

"AN SNN-INSPIRED VLSI ARCHITECTURE FOR REAL-TIME MYOCARDIAL INFARCTION DETECTION AND LOCALIZATION IN AMBULATORY WEARABLE DEVICES ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 11, page no.b519-b527, November-2025, Available :http://www.jetir.org/papers/JETIR2511167.pdf

"AN SNN-INSPIRED VLSI ARCHITECTURE FOR REAL-TIME MYOCARDIAL INFARCTION DETECTION AND LOCALIZATION IN AMBULATORY WEARABLE DEVICES ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 11, page no. ppb519-b527, November-2025, Available at : http://www.jetir.org/papers/JETIR2511167.pdf