Wearable Heart Attack Detection | Engineer Innovation
- A new technology developed at teh University of Mississippi promises too significantly reduce the time needed to detect heart attacks.
- Heart disease, a leading cause of death in the U.S., claims a life every 40 seconds due to a heart attack.
- The AI chip boasts 92.4% accuracy and is energy-efficient enough to be embedded in wearable technology.
A groundbreaking AI-powered chip is revolutionizing heart attack detection, offering a faster and more accurate diagnosis, which is crucial considering heart disease is a leading cause of death. This innovative technology, developed at the University of Mississippi, analyzes electrocardiograms (ECGs) in real-time, potentially doubling the speed of current methods. the team aims to integrate this advanced chip into wearable devices, enhancing accessibility and potentially saving lives. The chip achieves 92.4% accuracy and prioritizes energy efficiency,crucial for wearable integration. This project’s approach involves both hardware and software optimization, spearheaded by doctoral student Tamador Mohaidat and Md. Rahat Kader Khan. As News Directory 3 continues to report on technological advancements, explore how this technology might change the future of preventative care and what’s next for its creators.
AI-Powered Chip Offers Faster Heart Attack Detection
Updated June 8, 2025
A new technology developed at teh University of Mississippi promises too significantly reduce the time needed to detect heart attacks. Electrical and computer engineering assistant professor Kasem Khalil and his team have created an artificial intelligence (AI) powered chip that analyzes electrocardiograms (ECGs) in real-time, offering a faster and more accurate diagnosis.
Heart disease, a leading cause of death in the U.S., claims a life every 40 seconds due to a heart attack. The current detection methods often require a visit to a medical facility for an ECG or blood tests, adding critical delays. This new technology aims to address this issue by enabling rapid detection through wearable devices.
The AI chip boasts 92.4% accuracy and is energy-efficient enough to be embedded in wearable technology. Doctoral student Tamador Mohaidat, from Irbid, Jordan, focused on the artificial neural network, while Md. Rahat Kader Khan, a graduate student from Dhaka, Bangladesh, developed the device’s software.
“For this issue, a few minutes or even a few extra seconds is going to give this person the care they need before it becomes worse,” Khalil said. “Compared to traditional methods, our technology is up to two times faster, while still highly accurate.” He added that the design prioritizes a lightweight and economic device.
Mohaidat emphasized the potential life-saving impact: “This method will save lives becuase we can monitor the heart in real time.” Khan noted the lab’s focus on the entire product, hardware and software, leading to system optimization.
What’s next
Khalil and his team are continuing to develop the technology and explore its potential for detecting other health issues, including seizures and dementia. The focus remains on creating faster and more efficient diagnostic tools.