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A Literature Survey on Telecardiac Systems and Arrhythmia Classification
Abstract
Telemonitoring refers to the process of monitoring the
status of a patient at a distance using the audio, video and other
telecommunications and electronic information processing
technologies. It has become a huge task with rapidly advancing
technology and rapidly changing and evolving standards of medical care and development. The main objective of this literature review is to evaluate the efficacy of telemedicine interventions for health outcomes for cardiac patients. An overview about the state of the art in research on telemedicine and telecardiac systems in an international perspective is proposed in this paper
Keywords
References
Hamde S.T., Analysis and Interpretation of ECG Signal Using Wavelet
Transform, PhD Thesis, Indian Institute of Technology Roorkee,
Roorkee, 2001.
Carlson J., Johansson R. and Olsson S.B., Classification of
electrocardio- graphic P-wave morphology, IEEE Trans. Biomedical
Eng., April 2001, Vol. 48, No. 4, pp 401-405.
Bartolo A., Clymer B.D., Burgess R.C., Turnbull J.P., Golish J.A. and
Perry M.C., An arrhythmia detector and heart rate estimator for
overnight polysomnography studies, IEEE Trans. Biomed. Eng., May
, Vol. 48, pp. 513-521.
Botter E.A., Nascimento C.L., Jr. and Yoneyama T., A neural network
with asymmetric basis functions for feature extraction of ECG P waves,
IEEE Trans. Biomed. Eng., Sept. 2001, Vol. 12, pp. 1252-1255.
Almeida R., Martinez J.P., Olmos S., Rocha A.P. and Laguna P.,
Automatic delineation of T and P waves using a wavelet-based
multiscale approach, Proc. Int. Congress on Computational
Bioengineering (M. Doblare, M. Cerrolaza and H. Rodrigues, Eds.),
Spain, 2003, pp. 243-247.
Ravier P. and Buttelli O., Robust detection of QRScomplex using
Klauder wavelets, Proc. XII European Signal Processing Conf.
(EUSIPCO-2004), Vienna, Austria, Sept. 6-10, 2004, pp. 2199-2202.
Darrington J., Towards real time QRS detection: A fast method using
minimal pre-processing, Biomedical Signal Processing and Control,
, Vol. 1, pp. 169-176.
Kupeer K.Y., On significant maxima detection: a fine to coarse
algorithm, Proc. IEEE 13th Int. Conf. on Pattern Recognition, August
, Vol. 2, pp. 270-274.
Szi-WenChen, Hsiao-ChenChen, and Hsiao-Lung Chan, A real time
QRS detection method based on moving-averaging incorporating with
wavelet denoising, Computer Methods and Programs in Biomedicine,
, Vol. 62, pp. 187-195.
Hosseini H.G., Luo D. and Reynolds K.J., The comparison of different
feed forward neural network architectures for ECG signal diagnosis,
Medical Engineering and Physics, 2006, Vol. 28, pp. 372-378.
Meyer C., Garela J.F. and Harris M., Combining algorithms in automatic
detection of QRS complexes in ECG signals, IEEE Tran. Information
Technology in Biomedicine, 2006, Vol. 10, No. 3, pp. 468-476.
Arzeno N.M., Deng Z-D. and Poon C-S., Analysis of first derivative
based QRS detection algorithm, IEEE Trans. Biomedical Engineering,
, Vol. 55, No. 2, pp. 478-482.
Ghaffari A., Golbayani H. and Ghasemi M., A new mathematical based
QRS detector using continuous wavelet transform, Computers and
Electrical Engineering, 2008, Vol. 34, pp. 81-91.
Puero E., Sörnmo L. and Laguna P., QRS slopes for detection and
characterization of myocardial ischemia, IEEE Tran. Biomedical
Engineering, 2008, Vol. 55, No. 2, pp. 468-477.
Mitra S., Mitra M. and Chaudhuri B.B., Pattern defined heuristic rules
and directional histogram based online ECG parameter extraction,
Measurement, 2009, Vol. 42, No. 1, pp.150-156.
Mehta S.S. and Lingayat N.S., Identification of QRS complexes in 12-
lead electrocardiogram, Expert Systems with Applications, Jan. 2009,
Vol. 36, pp. 820-828.
Sayadi O. and Shamsollahi M.B., Multiadaptive bionic
wavelettransform: application to ECG denoising and baseline wanderingreduction, EURASIP Journal on Advances in Signal Processing, Vol.
, Article ID 41274, 11 pages, 2007. doi:10.1155/2007/41274.
Haiying Zhou, Kun Mean Hou, Laurent Gineste, Christophe De Vaulx,”
A New System Dedicated to Real-time Cardiac Arrhythmias Teleassistance
and Monitoring” Journal of Universal Computer Science, vol.
, no. 1 (2006), 30-44
Jos´e Garc´ıa a,∗, Jes´ us D. Trigoa, ´ Alvaro Alesancoa, Pedro
Serranob, Javier Mateoa, Robert S.H. Istepanianc,” Design and
evaluation of a wireless decision-support system for heart rate variability
study in haemodialysis follow-up procedures”, computer methods and
programs in biomedicine ( 2 0 0 7 ) 273–282
S. Kohila, K. Gowri, “A Novel Real-time Intelligent Tele Cardiology
System Using Wireless Technology to Detect Cardiac Abnormalities”,
International Journal of Scientific & Engineering Research Volume 2,
Issue 5, May-2011 1 ISSN 2229-5518
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