This paper presents the work of signal discrimination
specifically for Electrocardiogram (ECG) waveform. ECG signal is
comprised of P, QRS, and T waves in each normal heart beat to
describe the pattern of heart rhythms corresponds to a specific
individual. Further medical diagnosis could be done to determine any
heart related disease using ECG information. The emphasis on QRS
Complex classification is further discussed to illustrate the
importance of it. Pan-Tompkins Algorithm, a widely known
technique has been adapted to realize the QRS Complex
classification process. There are eight steps involved namely
sampling, normalization, low pass filter, high pass filter (build a band
pass filter), derivation, squaring, averaging and lastly is the QRS
detection. The simulation results obtained is represented in a
Graphical User Interface (GUI) developed using MATLAB.
 Aehlert, Barbara," ECGs made easy: pocket reference, 2nd ed., St. Louis,
M0: Mosby, 2002.
 Narayana K.V.L, "Basic detection of QRS variation in ECG using
MATLAB", Innovative Systems Design and Engineering, Vol. 2, No 7.
 J. Pan and W. Tompkins, "Real Time Algorithm detection for QRS" ,
IEEE Trans. Eng. Biomed Eng, 32(3), 1985, pp.230-236.
 Friesen, G. M., Jannett, T. C., Jadallah, M. A., Yates, S. L., Quint, S. R.,
Nagle, H. T. 1990. A comparison of the noise sensitivity of nine QRS
detection algorithms. IEEE Trans. Biomed.Eng., BME-37: pp. 85-97.
 Thakor, N. V., Webster, J. G., and Tompkins, W. J. 1983. "Optimal QRS
detector". Medical and Biological Engineering, pp. 343-50.
 Thakor, N. V., Webster, J. G., and Tompkins, W. J. 1984. Estimation of
QRS complex power spectra for design of a QRS filter. IEEE Trans.
Biomed. Eng., BME-31: pp. 702-05.
 I.L.Ahmad and N.A. Jumadi, "Medical Physiology-An Introduction", 1st
ed., UTHM Publisher, 2009.
 F. Portet, A.I.Hernandz and G. Carrault, "Description algorithm QRS
real time in variation context", "Med. Biol. Eng Computing, 2005, 43(3),
 A. Ebrahimzadeh and A. Khazee, "Premature detection reduction
ventricle use neural network (Multi Layer Perceptron) MLP: A
comparative study", Measurement Volume 43, Issue 1, 2010, pp. 103-