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The surge in health-medical information analysis using artificial intelligence is an exciting development in the field. While much research has focused on predicting and diagnosing diseases by uncovering relationships between various data features, there is a pressing need for further exploration into advanced AI techniques for analyzing Bio-Signal data, such as constant physiological records like Electroencephalography(EEG) and electrocardiography(ECG). This study delves into the classification of ECG into different arrhythmia types, highlighting the crucial role of early and accurate detection in identifying heart diseases and determining the most effective treatment options for patients. This groundbreaking research exemplifies the potential for Artificial Intelligence (AI) to revolutionize healthcare and save lives.

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Machine Vision and Biomedical Signal and Image Processing

  • 章节

  • 发表日期：

    2025年

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  • Asit Kumar Lenka,
  • Leena Das

摘要

The surge in health-medical information analysis using artificial intelligence is an exciting development in the field. While much research has focused on predicting and diagnosing diseases by uncovering relationships between various data features, there is a pressing need for further exploration into advanced AI techniques for analyzing Bio-Signal data, such as constant physiological records like Electroencephalography(EEG) and electrocardiography(ECG). This study delves into the classification of ECG into different arrhythmia types, highlighting the crucial role of early and accurate detection in identifying heart diseases and determining the most effective treatment options for patients. This groundbreaking research exemplifies the potential for Artificial Intelligence (AI) to revolutionize healthcare and save lives.