A convolutional attention transformer network for ECG beat classification
This work aims to improve automated ECG beat classification in accordance with the Association for the Advancement of Medical Instrumentation (AAMI)-recommended classes by learning both local morphological patterns and longer-range temporal dependencies from ECG segments. We develop a complete analysis pipeline using t...