• DocumentCode
    3194969
  • Title

    A feasibility research on waveform recognition algorithm based on geometric characteristics

  • Author

    Li Feng ; Chen Meili

  • Author_Institution
    Comput. Coll., Univ. of Donghua, Shanghai, China
  • fYear
    2013
  • fDate
    18-21 Dec. 2013
  • Firstpage
    243
  • Lastpage
    248
  • Abstract
    ECG analysis diagnosis system mainly consists of two phases: waveform recognition and intelligent diagnostics. In practical applications, the ECG waveform recognition is the key to the system. Accuracy and reliability of the detection determine the diagnosis and treatment of heart disease. There are a variety of detection ways mentioned in the relevant papers. In this paper, a waveform recognition algorithm based on geometric characteristics is proposed. At first the ECG signal is filtered by the digital filter such as Butterworth filter, mean filter and so on in this proposed method, and then its first derivative and second derivative are computed respectively, which we employ to determine the trend and to compute the optimum slope of each point. We recognize the peak, onset, offset of ECG waves combined with the geometric features. At last by computer simulation with the PTB diagnostic ECG database, the algorithm is feasible.
  • Keywords
    digital simulation; electrocardiography; filtering theory; medical signal processing; pattern recognition; Butterworth filter; ECG analysis diagnosis system; PTB diagnostic ECG database; computer simulation; digital filter; electrocardiogram; geometric characteristics; heart disease; mean filter; waveform recognition algorithm; Band-pass filters; Detection algorithms; Digital filters; Electrocardiography; Feature extraction; Market research; Prediction algorithms; ECG; PTB; geometric characteristics; waveform recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on
  • Conference_Location
    Shanghai
  • Type

    conf

  • DOI
    10.1109/BIBM.2013.6732497
  • Filename
    6732497