Scholarlink

Electrocardiography (ECG/EKG) is a useful and straightforward examination that allows for the assessment of different cardiac conditions by recording electrical impulses within the heart. The identification of abnormal cardiac activity is determined by the useful information obtained from the ECG signal. Noise signal elimination is essential to carefully analyze ECG signals. To demonstrate cardiac irregularities by analyzing the ECG signal, it is necessary to extract different characteristics. This article presents a new method to improve the efficiency of ECG signals by employing the invasive weed optimization (IWO) algorithm. The objective is to extract an optimized thresholding value. The effectiveness of the proposed approach was assessed by utilizing the MIT-BIH arrhythmia database containing 48 records. The proposed method showed advancements in terms of quicker detection and better performance compared to other contemporary modalities in similar circumstances. The proposed method demonstrated high performance with a sensitivity rate of 99.96%, positive productivity rate of 99.80%, accuracy rate of 99.20%, error rate of 0.628%, and an F-score of 0.995 as the overall average across all records.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Improvement the Performance of QRS Detection in ECG Signals Based on Optimized Thresholding Modeling Technique

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Sukaina A. AL-Bairmani,
  • Mustafa R. Ismael,
  • Haider J. Abd,
  • Najah M. Al Maimuri,
  • Nidhal A. Mohammed,
  • Luay A. AL-Azawi

摘要

Electrocardiography (ECG/EKG) is a useful and straightforward examination that allows for the assessment of different cardiac conditions by recording electrical impulses within the heart. The identification of abnormal cardiac activity is determined by the useful information obtained from the ECG signal. Noise signal elimination is essential to carefully analyze ECG signals. To demonstrate cardiac irregularities by analyzing the ECG signal, it is necessary to extract different characteristics. This article presents a new method to improve the efficiency of ECG signals by employing the invasive weed optimization (IWO) algorithm. The objective is to extract an optimized thresholding value. The effectiveness of the proposed approach was assessed by utilizing the MIT-BIH arrhythmia database containing 48 records. The proposed method showed advancements in terms of quicker detection and better performance compared to other contemporary modalities in similar circumstances. The proposed method demonstrated high performance with a sensitivity rate of 99.96%, positive productivity rate of 99.80%, accuracy rate of 99.20%, error rate of 0.628%, and an F-score of 0.995 as the overall average across all records.