SivannaKing/SEU-ASIC-IOT-ECGAI
Arrhythmia Detection Using Algorithm and Hardware Co-design for Neural Network Inference Accelerators
This project offers an energy-efficient solution for early arrhythmia detection. It takes raw electrocardiogram (ECG) data as input and provides a diagnosis of cardiac arrhythmias, leveraging deep neural networks to ensure better accuracy and adaptability than traditional methods. This is designed for medical device developers, researchers, and engineers working on intelligent health monitoring systems or clinical diagnostic tools.
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Use this if you are developing compact, low-power medical devices for real-time arrhythmia detection that require advanced deep learning capabilities.
Not ideal if you need a high-level software-only solution without any hardware co-design considerations.
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Jun 05, 2023
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