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Our research investigates Symlet analysis application in diagnosing heart dysfunction, specifically the application was made on ECG signals of 20 patients from Ibn Al-Nafees hospital for heart diseases. The process begins with Pan–Tompkins algorithm for detecting R peaks and then employing Symlet 4 coefficients to diagnose patients heart conditions, this approach successfully identified 7 patients with NSR, 9 patients with AF, and 4 patients with CHF, showing high accuracy in R peaks detection and Symlet coefficients analysis. These results highlight the potential of this approach as a promising method for ECG-based diagnosis of heart dysfunctions, providing valuable insight for further advancements in cardiac health monitoring and treatment.

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Symlet Analysis for ECG-Based Diagnosis of Heart Dysfunction

  • 会议论文

  • 发表日期：

    2025年

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  • Amjad Hibtallah Hamza,
  • Zainab Abdulsatar Abduljabar

摘要

Our research investigates Symlet analysis application in diagnosing heart dysfunction, specifically the application was made on ECG signals of 20 patients from Ibn Al-Nafees hospital for heart diseases. The process begins with Pan–Tompkins algorithm for detecting R peaks and then employing Symlet 4 coefficients to diagnose patients heart conditions, this approach successfully identified 7 patients with NSR, 9 patients with AF, and 4 patients with CHF, showing high accuracy in R peaks detection and Symlet coefficients analysis. These results highlight the potential of this approach as a promising method for ECG-based diagnosis of heart dysfunctions, providing valuable insight for further advancements in cardiac health monitoring and treatment.