Abstract
Paroxysmal Atrial Fibrillation (PAF) prediction viability is an open research line. The definition of new valid parameters for this task can be based on very heterogeneous features. Genetic Algorithms (GAs) automatically find a set of parameters to maximize the diagnosis capabilities of a scheme based on the K-nearest neighbours algorithm. This is an efficient way of generating a number of possible solutions for the problem of PAF prediction. The present paper illustrates how GAs, rather than a statistical study of the database can be used to select the parameters giving the best classification rates.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Cabin H.S.; Clubb K.S.; Hall C.; Perlmutter R.A.; Feinstein A.R.: “Risk of systemic embolization of atrial fibrillation without mitral stenosis”, Am. J. Cardiol., vol. 61, pp. 714–717, 1990.
Petersen P.; Godtfredsen J.: “Embolic complications in paroxysmal atrial fibrillation”, Stroke, vol. 17, pp. 622–626, 1986.
Ishimoto N, Ito M, Kinoshita M. Signal-averaged P-wave abnormalities and atrial size in patients with and without idiopathic paroxysmal atrial fibrillation. Am Herat J, 2000; 139:684–689.
Amar D, Roistacher N, Zhang H, Baum MS, Ginsburg I, Steinberg JS. Signal-averaged Pwave duration does not predict atrial fibrillation after thoracic surgery. Anesthesiology, 1999; 91:16–23.
Vikman S, Makikallio TH, Yli-Mayry S, Pikkujamsa S, Koivisto AM, Reinikainen P, Airaksinen KEJ, Huikuri HV. Altered complexity and correlation properties of R-R interval dynamics before the spontaneous onset of paroxysmal atrial fibrillation. Circulation, 1999; 100:2079–2084.
Hnathova K, Waktare JEP, Murgatroyd FD, Guo X, Baiyan X, Camm AJ, Malik M. Analysis of the cardiac rhythm preceding episodes of paroxysmal atrial fibrillation. Am Heart J. 1998; 135:1010–1019.
Kolb C, Nurnberger S, Ndrepepa G, Schreieck J, Zrenner B, Karch M, Schmitt C, Modes of initiation of paroxysmal atrial fibrillation an analysis of 157 spontaneously occurring episodes using 12-lead Holter monitoring. PACE, 2000; 23(4):607.
Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PCh, Mark RG, Mietus JE, Moody GB, Peng CK, Stanley HE. PhysioBank, PhysioToolkit, and Physionet: Components of a New Research Resource for Complex Physiologic Signals. Circulation 101(23):e215–e220 [Circulation Electronic Pages; http://circ.ahajournals.org/cgi/content/full/101/23/e215];2000, June 13.
F. deToro, A.F. Díaz, C. Gil, J. Ortega. AGEMM: Optimización Multimodal Paralela con Algoritmos Genéticos. Actas de las XII Jornadas de Paralelismo, Valencia, 2001.
Bäck, T.; Hammel, U.; Schwefel, H.-P.:“Evolutionary Computation: comments on the history and current state”. IEEE Trans. on Evol. Comp., Vol. 1, No. 1, pp. 3–17. Abril, 1997.
Mota S, Ros E, Fernández, F.J., Díaz A.F., Prieto, A.: ECG Parameter Characterization of Paroxysmal Atrial Fibrillation. (BSI2002), pp. 247–250, Como, Italy, June 2002.
Ros E., Mota S., Toro, F.J., Díaz A.F., Fernández F.J.: Paroxysmal Atrial Fibrillation: Automatic Diagnosis Algorithm based on not Fibrillating ECGs. (BSI2002), pp. 251–254, Como, Italy, June 2002.
François, O.:“An evolutionary strategy for global minimization and its Markov chain analysis”. IEEE Trans. on Evolutionary Computation, Vol. 2, No. 3, pp. 77–90. Sep., 1998.
B. Sareni and L. Krähenbühl, “Fitness Sharing and Niching Methods Revisited”. IEEE Transaction on Evolutionary Computation, Vol 2, No. 3, 1998.
Cantü-Paz, E.:“A survey or Parallel Gas”. Informe Técnico IlliGAL R.97003, 1997.
S.W. Mahfoud, “A Comparison of Parallel and Sequencial Niching Methods”, Sixth Int. Conference on Genetic Algorithms, Morgan Kauffman, San Mateo, CA, 1995.
Devijver, PA y Kittler, JV. Pattern Recognition. A Statistical Approach, Prentice Hall-Englewood Cliffs 1982.
GB Moody, AL, Goldberger, S. McClennen, SP Swiryn, “Predicting the Onset of Paroxysmal Atrial Fibrillation: The Computers in Cardiology Challenge 2001”, Computers in Cardiology 2001, Rotterdam, pp. 113–116, 2001.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mota, S., Ros, E., de Toro, F., Ortega, J. (2003). Genetic Algorithm applied to Paroxysmal Atrial Fibrillation Prediction. In: Mira, J., Álvarez, J.R. (eds) Artificial Neural Nets Problem Solving Methods. IWANN 2003. Lecture Notes in Computer Science, vol 2687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44869-1_44
Download citation
DOI: https://doi.org/10.1007/3-540-44869-1_44
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40211-4
Online ISBN: 978-3-540-44869-3
eBook Packages: Springer Book Archive