FILTERING DATA DISKRIT ELEKTROKARDIOGRAM UNTUK PENENTUAN PQRST DALAM SATU SIKLUS
Sari
sedangkan pergeseran mundur durasi 0.5dR dari RN+1 akan didapatkan titik akhir siklus. Peak P digunakan untuk
merepresentasikan keadaan depolarisasi Atrium, QRS digunakan untuk menunjukkan depolarisasi ventrikel dan peak T digunakan untuk menunjukkan kondisi repolarisasi dalam otot-otot Jantung. Data diskrit dari Physionet MIT-BIH dan hasil pengukuran sendiri memakai ECGd 12-lead digunakan sebagai data untuk memperoleh nilai peak PQRST dalam tiap siklus
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Ali Zifan, et.al, 2005. Automated ECG segmentation
using piecewise derivative dynamic time
warping, International journal of Biological
and life science 1:3 2005
Andreas S, et.al, 1998. Analysis of beat to beat
variability of frequency contens in the
Electrocardiogram using two-dimensional
Fourier Transform. IEEE transactions on
Biomedical Engineering, vol.45, No.2,
February 1998
Ashish Birle, Suyog Malviya, Deepak Mittal, 2015.
A novel technique of R-peak detection for
ECG signal analysis : variable threshold
method. International Journal of Advanced
Research in Electronics and Communication
Engineering (IJARECE), vol.4, issue 5, May
David Prutchi, Michael Norris. 2005. Design and
Development of Medical Electronic
Instrument. A John Wiley & Sons, Inc.,
Publication
Deboleena S and Madhuchhanda M, 2012. R-peak
detection algorithm for ECG using double
difference and RR interval processing.
SciVerse ScienceDirect Elsevier, Procedia
Technology 4 (2012) 873-877
FU Huwez, PW Macfarlane, 2003. Assesment of
selected ECG voltage criteria for
abnormality in Eccentric and Concentric left
ventricular hypertrophy. IEEE Computer in
Cardiology, 2003;30:57-59
Guyton. Arthur & Hall.E , 2008, Textbook of
Medical Physiology, 11th edition, Elsevier,
SingaporeHussain A Jaber AL, Ziarjawey and Cankaya, 2015.
Heart rate monitoring and PQRST detection
based on graphical user interface with
Matlab. International Journal of Information
and Electronics Engineering, vol.5, No.4,
July 2015
Kamalapriya M and Renulakshmi R, 2012.
Electrrocardiogram signal analysis using
zoom FFT. IEEE Biosignal and biorobotics
conference (BRC), 2012
Mohammad Rakibul Islam, et.all, 2015. Arrhythmia
detection technique using basic ECG
parameters. International journal of
Computer Applications (0975-8887) vol.119,
No.10,June 2015
Muttaqin A Ahmad, Budi Yuli S, 2009. Pocket ECG,
“How to learn ECG from zero”, Penerbit
Intan Cendikia, Yogyakarta. ISBN
No.979985718-3
PA Otubu, For the Realisation of the design of
Electrocardiogram for the Monitoring of the
Physiology of Human Heart, Journal of
Engineering and Applied Sciences
(11):856-860, 2008. ISSN:1816-
X,@Medwell Journals, 2008
Rashid GA, Mohammad AT, 2015. ECG based
detection of left ventricular hypertrophy
using higher order statistics. IEEE 2015 23rd
Iranian Conference on Electrical Engineering
(ICEE)
Sabar S, Rasjad I, Djanggan S, Setyawan S, Using
Discrete data of ECG in the Numerical and
Spectral forms, International Journal of
Electrical & Computer Sciences, IJECSIJENS, vol.15, No.03, June 2015
Sabar S, Rasjad I, Djanggan S, Setyawan S,
Determining the ECG 1 cycle wave using
dicrete data, Journal of Theoretical and
Applied Information Technology, Jatit,
vol.88, No.1, June 2016
Sachin Singh, Netaji Gandhi, Pattern analysis of
different ECG signal using Pan-Tompkin’s
algorithm, International Journal on Computer
Science and Engineering (IJCSE), vol.02,
no.07, 2010, 2502-2505
Thulasi Prasad S & Varadarajan S, 2015. Analysis of
ST-Segment abnormalitiesin ECG using
signal block averaging Technique.
International Journal of Advanced Research
in Computer and Communication
Engineering, vol.4, Issue 2, February 2015
Vivek SC, Durgesh KM, PB Patil, 2011. Assessment
of selected Electrocardiogram voltage
criteria for left ventricular hypertrophy by
using SPSS. IEEE First International
Conference on Informatics and
Computational Intelligence, 978-0-7695-
-6/11. DOI 10.1109/ICI.2011.69
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