Artifcial Intelligence-Enabled Wearable ECG for Elderly Patients

Abstract

In this chapter, we propose ResNet50, a deep learning model that uses a pooled dataset of 42 511 ECG 12-Lead records to categorize 26 CVD and normal sinus rhythm. When compared to the values obtained in the literature, our proposed model reaches 99.99% accuracy and precision. This result demonstrates the effcacy of the proposed model. ResNet50 will be used as a platform for diagnosing ECG signals and assisting cardiologists in their work in the future.