ArticleComputer methods and programs in biomedicine2021
ECG Language processing (ELP): A new technique to analyze ECG signals.
Article in Computer methods and programs in biomedicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 3 citations in OpenAlex.
- An enhanced hypergraph CNN with adaptive focal loss for automated ECG heartbeat classification.Scientific reports · 2026Article
- Bridging clinical knowledge and AI: an interpretable transformer framework for ECG diagnosis.NPJ digital medicine · 2025Article
- Unveiling Hearts: Deep Learning-Based Electrocardiogram Classification for Congenital Heart Disease Detection.Current medical science · 2025Article
- Article
- Ensemble classifier fostered detection of arrhythmia using ECG data.Medical & biological engineering & computing · 2023Article
- Single-arm diagnostic electrocardiography with printed graphene on wearable textiles.Sensors and actuators. A, Physical · 2023Article
- State-of-the-Art Deep Learning Methods on Electrocardiogram Data: Systematic Review.JMIR medical informatics · 2022Review
- Golden Standard or Obsolete Method? Review of ECG Applications in Clinical and Experimental Context.Frontiers in physiology · 2022Review
- Nurse Staffing Practices and Postoperative Atrial Fibrillation Among Cardiac Surgery Patients: A Multisite Cohort Study.CJC open · 2022Article
- Advanced Bioelectrical Signal Processing Methods: Past, Present and Future Approach-Part I: Cardiac Signals.Sensors (Basel, Switzerland) · 2021Review
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Authors and funding
4 authors at 2 institutions in 3 countries.
Funding
Abstract
backgroundA language is constructed of a finite/infinite set of sentences composing of words. Similar to natural languages, the Electrocardiogram (ECG) signal, the most common noninvasive tool to study the functionality of the heart and diagnose several abnormal arrhythmias, is made up of sequences of three or four distinct waves, including the P-wave, QRS complex, T-wave, and U-wave. An ECG signal may contain several different varieties of each wave (e.g., the QRS complex can have various appearances). For this reason, the ECG signal is a sequence of heartbeats similar to sentences in natural languages) and each heartbeat is composed of a set of waves (similar to words in a sentence) of different morphologies.
methodsAnalogous to natural language processing (NLP), which is used to help computers understand and interpret the human's natural language, it is possible to develop methods inspired by NLP to aid computers to gain a deeper understanding of Electrocardiogram signals. In this work, our goal is to propose a novel ECG analysis technique, ECG language processing (ELP), focusing on empowering computers to understand ECG signals in a way physicians do.
resultsWe evaluated the proposed approach on two tasks, including the classification of heartbeats and the detection of atrial fibrillation in the ECG signals. Overall, our technique resulted in better performance or comparable performance with smaller neural networks compared to other deep neural networks and existing algorithms.
conclusionExperimental results on three databases (i.e., PhysioNet's MIT-BIH, MIT-BIH AFIB, and PhysioNet Challenge 2017 AFIB Dataset databases) reveal that the proposed approach as a general idea can be applied to a variety of biomedical applications and can achieve remarkable performance.
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