Deep Learning-based Personalized ECG Monitor

초록

Early detection of cardiovascular disease through electrocardiogram monitoring is becoming increasingly important to prevent serious heart disease. This paper presents a method to monitor electrocardiograms in real time by implementing artificial intelligence technology on IoT devices. Since the edge device used in this paper has limited resources, the TensorFlow Lite which is specially designed to support real-time machine learning (ML) inference on low-power and resource-constrained edge devices was used. The performance of the pre-trained model and the lightweight model was compared through TensorFlow Lite to confirm whether the application was suitable.