Open Science Research Excellence
@article{(International Science Index):,
  title    = {ROC Analysis of PVC Detection Algorithm using ECG and Vector-ECG Charateristics},
  author    = {J. S. Nah and  A. Y. Jeon and  J. H. Ro and  G. R. Jeon},
  country   = {},
  abstract  = {ECG analysis method was developed using ROC
analysis of PVC detecting algorithm. ECG signal of MIT-BIH
arrhythmia database was analyzed by MATLAB. First of all, the
baseline was removed by median filter to preprocess the ECG signal.
R peaks were detected for ECG analysis method, and normal VCG
was extracted for VCG analysis method. Four PVC detecting
algorithm was analyzed by ROC curve, which parameters are
maximum amplitude of QRS complex, width of QRS complex, r-r
interval and geometric mean of VCG. To set cut-off value of
parameters, ROC curve was estimated by true-positive rate
(sensitivity) and false-positive rate. sensitivity and false negative rate
(specificity) of ROC curve calculated, and ECG was analyzed using
cut-off value which was estimated from ROC curve. As a result, PVC
detecting algorithm of VCG geometric mean have high availability,
and PVC could be detected more accurately with amplitude and width
of QRS complex.},
    journal   = {International Journal of Medical, Health, Biomedical, Bioengineering and Pharmaceutical Engineering},  volume    = {6},
  number    = {1},
  year      = {2012},
  pages     = {6 - 8},
  ee        = {},
  url       = {},
  bibsource = {},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 61, 2012},