• DocumentCode
    677230
  • Title

    High speed approach for detecting QRS complex characteristics in single lead electrocardiogram signal

  • Author

    Salih, Sameer K. ; Aljunid, S.A. ; Aljunid, Syed M. ; Maskon, Oteh ; Yahya, A.

  • Author_Institution
    Comput. & Commun. Sch., Univ. Malaysia Perlis, Arau, Malaysia
  • fYear
    2013
  • fDate
    Nov. 29 2013-Dec. 1 2013
  • Firstpage
    391
  • Lastpage
    396
  • Abstract
    The extracted features from the QRS complex in the electrocardiogram (ECG) signal are considered mainly in the heart rate evaluation and cardiac disease diagnosis. In this paper, high speed approach named “Rising Falling Transition Method (RFTM)” is proposed to detect the characteristics of QRS complex in single lead ECG signal. The proposed approach applies single straight forward algorithm with two stages. The first stage takes the advantage of the transition from rising to falling edge inside each QRS complex as a base to determine the time locations of the vertices in a triangle that composes from the Q-wave end, R-wave peak, and S-wave onset. The second stage determines the time location of Q-wave onset and S-wave end (J-point) using a linear scan along short period which starts from Q-wave end and S-wave onset towards the target end points at Q-wave onset and S-wave end, respectively. The detector approach is able to detect QRS complex of different morphologies (wide/small interval, high/low amplitude, and negative polarities). The detection performance of the proposed approach is evaluated on a single channel of some annotated records from the QT database which collected from seven ECG categories and 48 annotated records from MIT-BIH database. Simulation results show that the average detection rates of sensitivity (Se) and specificity (Sp) are 99.84% and 99.94%, respectively for MIT-BIH Arrhythmia database. The validation results prove the reliability and accuracy of proposed RFTM approach.
  • Keywords
    diseases; electrocardiography; feature extraction; medical signal processing; patient diagnosis; sensitivity; ECG categories collection; J-point; MIT-BIH arrhythmia database; Q-wave end; Q-wave onset; QRS complex characteristics detection; R-wave peak; S-wave onset; annotated records; cardiac disease diagnosis; feature extraction; heart rate evaluation; high-low amplitude; high-speed approach; negative polarities; rising falling transition method; sensitivity; single lead ECG signal; single lead electrocardiogram signal; time locations; wide-small interval; Algorithm design and analysis; Conferences; Control systems; Databases; Electrocardiography; Image edge detection; Radiation detectors; MIT-BIH Arrhythmia and QT databases; QRS complex detection; RFTM; Rising and Falling edge transition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control System, Computing and Engineering (ICCSCE), 2013 IEEE International Conference on
  • Conference_Location
    Mindeb
  • Print_ISBN
    978-1-4799-1506-4
  • Type

    conf

  • DOI
    10.1109/ICCSCE.2013.6719996
  • Filename
    6719996