ECG abnormality detection algorithm

Soha Ahmed, Ali Hilal-Alnaqbi, Mohamed Al Hemairy, Mahmoud Al Ahmad

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


The monitoring and early detection of abnormalities in the cardiac cycle morphology have significant impact on the prevention of heart diseases and their associated complications. Electrocardiogram (ECG) is very effective in detecting irregularities of the heart muscle functionality. In this work, we investigate the detection of possible abnormalities in ECG signal and the identification of the corresponding heart disease in real-time using an efficient algorithm. The algorithm relies on cross-correlation theory to detect abnormalities in ECG signal. The algorithm incorporates two cross-correlations steps. The first step detects abnormality in a real-time ECG signal trace while the second step identifies the corresponding disease. The optimization of search-time is the main advantage of this algorithm.

Original languageEnglish
Pages (from-to)215-219
Number of pages5
JournalInternational Journal of Advanced Computer Science and Applications
Issue number8
Publication statusPublished - 2018


  • Abnormalities detection
  • Algorithm
  • Cardiac cycle
  • Cross-correlation
  • EHealth
  • Electrocardiogram (ECG)
  • Remote monitoring

ASJC Scopus subject areas

  • General Computer Science


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