ECGformer: Leveraging transformer for ECG heartbeat arrhythmia classification

An arrhythmia, also known as a dysrhythmia, refers to an irregular heartbeat.There are various types of arrhythmias that can originate from different areasof the heart, resulting in either a rapid, slow, or irregular heartbeat. Anelectrocardiogram (ECG) is a vital diagnostic tool used to detect heartirregularities and abnormalities, allowing experts to analyze the heart’selectrical signals to identify intricate patterns and deviations from the norm.Over the past few decades, numerous studies have been conducted to developautomated methods for classifying heartbeats based on ECG data. In recentyears, deep learning has demonstrated exceptional capabilities in tacklingvarious medical challenges, particularly with transformers as a modelarchitecture for sequence processing. By leveraging the transformers, wedeveloped the ECGformer model for the classification of various arrhythmiaspresent in electrocardiogram data. We assessed the suggested approach using theMIT-BIH and PTB datasets. ECG heartbeat arrhythmia classification results showthat the proposed method is highly effective.

Further reading#

• Access Paper in arXiv.org