Cardiac pulse modeling using a modified van der Pol oscillator and genetic algorithms. Lopez-Chamorro, F., M., Arciniegas-Mejia, A., F., Imbajoa-Ruiz, D., E., Rosero-Montalvo, P., D., García, P., Castro-Ospina, A., E., Acosta, A., & Peluffo-Ordóñez, D., H. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 10813 LNBI, pages 96-106, 2018.
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This paper proposes an approach for modeling cardiac pulses from electrocardiographic signals (ECG). A modified van der Pol oscillator model (mvP) is analyzed, which, under a proper configuration, is capable of describing action potentials, and, therefore, it can be adapted for modeling a normal cardiac pulse. Adequate parameters of the mvP system response are estimated using non-linear dynamics methods, like dynamic time warping (DTW). In order to represent an adaptive response for each individual heartbeat, a parameter tuning optimization method is applied which is based on a genetic algorithm that generates responses that morphologically resemble real ECG. This feature is particularly relevant since heartbeats have intrinsically strong variability in terms of both shape and length. Experiments are performed over real ECG from MIT-BIH arrhythmias database. The application of the optimization process shows that the mvP oscillator can be used properly to model the ideal cardiac rate pulse.
@inproceedings{
 title = {Cardiac pulse modeling using a modified van der Pol oscillator and genetic algorithms},
 type = {inproceedings},
 year = {2018},
 pages = {96-106},
 volume = {10813 LNBI},
 id = {d7886035-2b70-3031-a49d-cd1c73d07ea8},
 created = {2018-05-02T22:57:38.367Z},
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 profile_id = {f01ceea9-1014-347a-b89d-aa69782ea2ee},
 last_modified = {2021-10-05T13:36:21.176Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {This paper proposes an approach for modeling cardiac pulses from electrocardiographic signals (ECG). A modified van der Pol oscillator model (mvP) is analyzed, which, under a proper configuration, is capable of describing action potentials, and, therefore, it can be adapted for modeling a normal cardiac pulse. Adequate parameters of the mvP system response are estimated using non-linear dynamics methods, like dynamic time warping (DTW). In order to represent an adaptive response for each individual heartbeat, a parameter tuning optimization method is applied which is based on a genetic algorithm that generates responses that morphologically resemble real ECG. This feature is particularly relevant since heartbeats have intrinsically strong variability in terms of both shape and length. Experiments are performed over real ECG from MIT-BIH arrhythmias database. The application of the optimization process shows that the mvP oscillator can be used properly to model the ideal cardiac rate pulse.},
 bibtype = {inproceedings},
 author = {Lopez-Chamorro, Fabián M. and Arciniegas-Mejia, Andrés F. and Imbajoa-Ruiz, David Esteban and Rosero-Montalvo, Paul D. and García, Pedro and Castro-Ospina, Andrés Eduardo and Acosta, Antonio and Peluffo-Ordóñez, Diego Hernán},
 doi = {10.1007/978-3-319-78723-7_8},
 booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
}

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