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Revolutionizing Cardiac Care: A Comprehensive Review of ECG-Based Arrhythmia Prediction Techniques

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Data Science and Applications (ICDSA 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 818))

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Abstract

Cardiac arrhythmia has now become a common condition that affects millions of people worldwide. Arrhythmia can be detected and anticipated early, allowing for more effective treatment and better comprehension of the results. The various machine learning–based methods for detecting various cardiac arrhythmias are reviewed in this investigation. An enormous assortment of electrocardiogram (ECG) information from people with different arrhythmias was utilized to prepare the models broke down in this review. The studies employ various machine learning and deep learning methods to accurately diagnose arrhythmia and comprehend intricate patterns in electrocardiogram (ECG) data. In addition, we investigate how various electrocardiogram (ECG) signal qualities affect the performance of various models. This research takes the employed studies into consideration and compare their results.

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Authors and Affiliations

  1. Department of CSE, Chandigarh University, Gharuan, Punjab, India

    Akhil Dhiman, Raj Kumar, Harsh Karki & Pawan Yadav

Authors
  1. Akhil Dhiman
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  2. Raj Kumar
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  3. Harsh Karki
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  4. Pawan Yadav
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Corresponding author

Correspondence to Akhil Dhiman .

Editor information

Editors and Affiliations

  1. Department of Electronics and Communication Engineering, Malaviya National Institute of Technology, Jaipur, Rajasthan, India

    Satyasai Jagannath Nanda

  2. Department of Electronics and Communication Engineering, Malaviya National Institute of Technology, Jaipur, Rajasthan, India

    Rajendra Prasad Yadav

  3. Department of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW, Australia

    Amir H. Gandomi

  4. Department of Computer Science and Engineering and Information Technology, Jaypee Institute of Information Technology, Noida, Uttar Pradesh, India

    Mukesh Saraswat

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Dhiman, A., Kumar, R., Karki, H., Yadav, P. (2024). Revolutionizing Cardiac Care: A Comprehensive Review of ECG-Based Arrhythmia Prediction Techniques. In: Nanda, S.J., Yadav, R.P., Gandomi, A.H., Saraswat, M. (eds) Data Science and Applications. ICDSA 2023. Lecture Notes in Networks and Systems, vol 818. Springer, Singapore. https://doi.org/10.1007/978-981-99-7862-5_38

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