Publications by authors named "Celal Alagoz"

3 Publications

  • Page 1 of 1

Complexity reduction in human atrial modeling using extended Kalman filter.

Med Biol Eng Comput 2019 Apr 6;57(4):777-794. Epub 2018 Nov 6.

Electrical and Computer Engineering Department, Drexel University, Philadelphia, PA, USA.

Human atrial tissue electrophysiology is modeled upon biophysical details obtained from cellular level measurements. Data collected for this purpose typically represent a unique state of the tissue. As reproducing dynamic cases such as subject-varied and/or disorder-varied electrophysiological properties is in question, such complex models are typically hard to use. Hence, there is a need for simpler yet biophysically accurate and mathematically tractable models to be used for case-specific reproductions and simulations. In this study, a scheme for parameter estimation of a phenomenological cardiac model to match a targeted behavior generated from a complex model is used. Specifically, an algorithm incorporating extended Kalman filter (EKF) into the scheme is proposed. Its performance is then compared to that of particle swarm optimization (PSO) and sequential quadratic programming (SQP), algorithms that have been widely used for parameter optimization. Both robustness and adaptability performance of the algorithms are tested through various designs. For this, reproducing action potential (AP) waveforms of varying remodeling states of atrial fibrillation (AF) at different stimulus protocols was targeted. Also, randomly generated initial parameter sets are included in the tests. In addition, AP duration (APD) restitution curve (RC) is used for a multiscale evaluation of fitting performance. Finally, wavefront propagation on 2D of a selected AF remodeling state using parameter solutions from each of the algorithms is simulated for a qualitative evaluation. In general, PSO yielded superior performances than EKF and SQP with respect to fitting AP waveforms. Considering both AP and APD RC, however, EKF yielded the best accuracies. Also, more accurate spiral wave reentry is obtained with EKF. Overall, EKF algorithm yielded the best performance in robustness and adaptability. Graphical Abstract.
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http://dx.doi.org/10.1007/s11517-018-1921-1DOI Listing
April 2019

Spiral waves characterization: Implications for an automated cardiodynamic tissue characterization.

Comput Methods Programs Biomed 2018 Jul 11;161:15-24. Epub 2018 Apr 11.

ECE Department, Drexel University, Philadelphia, PA 19104, USA. Electronic address:

Background And Objective: Spiral waves are phenomena observed in cardiac tissue especially during fibrillatory activities. Spiral waves are revealed through in-vivo and in-vitro studies using high density mapping that requires special experimental setup. Also, in-silico spiral wave analysis and classification is performed using membrane potentials from entire tissue. In this study, we report a characterization approach that identifies spiral wave behaviors using intracardiac electrogram (EGM) readings obtained with commonly used multipolar diagnostic catheters that perform localized but high-resolution readings. Specifically, the algorithm is designed to distinguish between stationary, meandering, and break-up rotors.

Methods: The clustering and classification algorithms are tested on simulated data produced using a phenomenological 2D model of cardiac propagation. For EGM measurements, unipolar-bipolar EGM readings from various locations on tissue using two catheter types are modeled. The distance measure between spiral behaviors are assessed using normalized compression distance (NCD), an information theoretical distance. NCD is a universal metric in the sense it is solely based on compressibility of dataset and not requiring feature extraction. We also introduce normalized FFT distance (NFFTD) where compressibility is replaced with a FFT parameter.

Results: Overall, outstanding clustering performance was achieved across varying EGM reading configurations. We found that effectiveness in distinguishing was superior in case of NCD than NFFTD. We demonstrated that distinct spiral activity identification on a behaviorally heterogeneous tissue is also possible.

Conclusions: This report demonstrates a theoretical validation of clustering and classification approaches that provide an automated mapping from EGM signals to assessment of spiral wave behaviors and hence offers a potential mapping and analysis framework for cardiac tissue wavefront propagation patterns.
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http://dx.doi.org/10.1016/j.cmpb.2018.04.006DOI Listing
July 2018

Spiral wave classification using normalized compression distance: Towards atrial tissue spatiotemporal electrophysiological behavior characterization.

Annu Int Conf IEEE Eng Med Biol Soc 2015 Aug;2015:4503-6

Analysis of electrical activation patterns such as re-entries during atrial fibrillation (Afib) is crucial in understanding arrhythmic mechanisms and assessment of diagnostic measures. Spiral waves are a phenomena that provide intuitive basis for re-entries occurring in cardiac tissue. Distinct spiral wave behaviors such as stable spiral waves, meandering spiral waves, and spiral wave break-up may have distinct electrogram manifestations on a mapping catheter. Hence, it is desirable to have an automated classification of spiral wave behavior based on catheter recordings for a qualitative characterization of spatiotemporal electrophysiological activity on atrial tissue. In this study, we propose a method for classification of spatiotemporal characteristics of simulated atrial activation patterns in terms of distinct spiral wave behaviors during Afib using two different techniques: normalized compressed distance (NCD) and normalized FFT (NFFTD). We use a phenomenological model for cardiac electrical propagation to produce various simulated spiral wave behaviors on a 2D grid and labeled them as stable, meandering, or breakup. By mimicking commonly used catheter types, a star shaped and a circular shaped both of which do the local readings from atrial wall, monopolar and bipolar intracardiac electrograms are simulated. Virtual catheters are positioned at different locations on the grid. The classification performance for different catheter locations, types and for monopolar or bipolar readings were also compared. We observed that the performance for each case differed slightly. However, we found that NCD performance is superior to NFFTD. Through the simulation study, we showed the theoretical validation of the proposed method. Our findings suggest that a qualitative wavefront activation pattern can be assessed during Afib without the need for highly invasive mapping techniques such as multisite simultaneous electrogram recordings.
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http://dx.doi.org/10.1109/EMBC.2015.7319395DOI Listing
August 2015
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