... pp. 433 – 436 .
[34 ] Maglaveras, N., et al., ECG Pattern Recognition and Classification Using Non-Linear
Transformations and Neural Networks: A Review,” International Journal of Medical
Informatics, ... Press,
2000.
[1 03] Ivanov, P. C., et al., “Scaling Behaviour of Heartbeat Intervals Obtained by Wavelet-
Based Time-Series Analysis, ” Nature, Vol. 38 3, September 1996, pp. 32 3 32...
... 1965, pp. 32 1 33 3.
[19] Abarbanel, H. D. I., R. Brown, and M. B. Kennel, “Local Lyapunov Exponents Computed
from Observed Data, ” Journal of Nonlinear Science, Vol. 2, No. 3, 1992, pp. 34 3 36 5.
[20] ... classified TWA de-
tection into preprocessing, data reduction, and analysis stages. This section focuses
upon the strengths and limitations of TWA analysis methods, broadl...
... incorporate time-domain
analysis [3 5], the KLT approach [7], a combination of time-domain analysis and
KLT approach [37 ], a neural network approach [17], and a combination of the
KLT transform and a neural ... with standard algorithms. For the analysis of 10-second
12-lead ECG signals, this is rarely an issue. However, when very large amounts
of ECG data must be processe...
... for Generating and Managing ecgML-Based Infor-
mation,” Computers in Cardiology, Vol. 31 , 2004, pp. 5 73 576.
[33 ] Schneider, R., libRASCH, http://www.librasch.org/.
[34 ] ANSI/AAMI-EC38, Ambulatory ... 11 :39 Chan-Horizon Azuaje˙Book
3. 3 Standard Clinical ECG Features 61
Figure 3. 6 Standard fiducial points in the ECG (P, Q, R, S, T, and U) together with clinical features
(...
... 108], compres-
sion and filtering [119, 1 23] , and classification [124]. However, the required com-
plexity for realistic models (particularly for ECG generation) has limited the devel-
opment of ... Relationship Between π In-
terval and Systolic Blood Pressure Fluctuations: A Frequency-Dependent Phenomenon,”
Cardiovascular Research, Vol. 38 , 1998, pp. 33 2 33 9.
[22] Mukkamal...
... Filtering Methods
Figure 5.8 Layout of a D-p-D auto-associative neural network.
inputs and outputs; the target data vector is simply the input data vector. There-
fore, no labeling of training data ... H., and H. Heinrich, Analysis of ECG Late Potentials Using Time-Frequency
Methods, ” in M. Akay, (ed.), Time Frequency and Wavelets in Biomedical Signal Process-
ing, Chapter...
... Prin-
cipal Component Analysis, ” Journal of Ambulatory Monitoring, Vol. 5, No. 2 3, 19 93,
pp. 167–1 73.
[18] Garc
´
ia, J., et al., “Comparative Study of Local and Karhunen-Lo
`
eve-Based ST-T ... which are visually informative and accessible for analysis at any time instant.
Therefore, a technique which converts such point event series into a form suitable
for standard analys...