1732-3916 DPAR grammars for ECG diagnosis justification Flasiński Piotr author IT Systems Department, Jagiellonian University, ul. St. Łojasiewicza 4, Cracow 30-384 (Cooperation) Correspondence to: Piotr Flasiński 16 02 2018 Volume 26 2017 37 47 Copyright © 2018 2018 <p style="text-align: left;">A novel model of dynamically programmed attributed regular grammars, DPAR, for the ECG diagnosis justification purposes is presented in the paper. A formal model, power properties and a case of DPAR grammar are described. The formalism of DPAR grammars allows to differentiate between certain subclasses of ECG phenomena.</p> [1] Belferte G., De Mori R., Ferraris F., A contribution to the automatic processing of electrocardiograms using syntactic methods. IEEE Trans. Biomed. Eng., 1979, 26, pp. 125-136. [2] Bunke H.O., Sanfeliu A. (eds.), Syntactic and Structural Pattern Recognition - Theory and Applications. World Scientific, Singapore, 1990. [3] Cianciolo A.T., Williams R.G., Klamen D.L., Roberts N.K., Biomedical knowledge, clinical cognition and diagnostic justification: a structural equation model. Medical Education, 2013, 47, pp. 309-316. [4] Flasi´nski M., Flasi´nski P., Konduracka E., On the use of programmed automata for verification of ECG diagnoses. Advances in Intelligent Systems and Computing 226, Springer, Berlin-Heidelberg-New York, 2013, pp. 591–599. [5] Flasi´nski P., Syntactic pattern recognition of ECG for diagnostic justification. Machine Graphics &amp; Vision International Journal, 2014, 24, 3/4, pp. 43–55. [6] Fu K.S., Syntactic Pattern Recognition and Applications. Prentice Hall, Englewood Cliffs, 1982. [7] Gilhooly K.J., McGeorge P., Hunter J. et al., Biomedical knowledge in diagnostic thinking: the case of electrocardiogram (ECG) interpretation. European Journal of Cognitive Psychology, 1997, 9, pp. 199–223. [8] Gonzales R.C., Thomason M.G., Syntactic Pattern Recognition: An Introduction. Addison-Wesley, Reading, 1978. [9] Horowitz S.L., A syntactic algorithm for peak detection in waveforms with applications to cardiography. Comm. ACM, 1975, 18, pp. 281–285. [10] Kolykhalov I.V., Iznak, A.F., Chayanov N.V. et al., EEG mapping in diagnostic assessment of patients with mild dementia. European Neuropsychopharmacology, 1997, 7, pp. 248. [11] Koski A., Juhola M., Meriste M., Syntactic recognition of ECG signals by attributed finite automata. Pattern Recognition, 1995, 28, pp. 1927–1940. [12] McLaughlin K.J.,The Contribution of Analytic Information Processing to Diagnostic Performance in Medicine, Ph.D. Thesis, Erasmus University Rotterdam, 2007. [13] Papakonstantinou G., Skordalakis E., Gritzali F., An attribute grammar for QRS detection. Pattern Recognition, 1986, 19, pp. 297–303. [14] Patel V., Groen G., Knowledge based solution strategies in medical reasoning. Cognitive Science, 1986, 10, pp. 91–116. [15] Pavlidis T., Structural Pattern Recognition. Springer, New York, 1997. [16] Pi¸etka E., Feature extraction in computerized approach to the ECG analysis. Pattern Recognition 1991, 24, pp. 139–146. [17] Skordalakis E., Syntactic ECG processing: a review. Pattern Recognition 1986, 19, pp. 305–313, . [18] Stallmann F.W., Pipberger H.V., Automatic recognition of electrocardiographic waves by digital computer. Circ. Res., 1961, 9, pp. 1138–1143. [19] Tadeusiewicz R., Ogiela M.R., Medical Image Understanding Technology. Springer, Berlin-Heidelberg-New York, 2004. [20] Trahanias P., Skordalakis E., Syntactic pattern recognition of the ECG. IEEE Trans. Patt. Analysis Mach. Intell., 1990, 12, pp. 648–657. [21] Tumer M.B., Belfore L.A., Ropella K.M., A syntactic methodology for automatic diagnosis by analysis of continuous time measurements using hierarchical signal representations. IEEE Trans. on Syst. Man Cybern., 2003, 33, pp. 951–965. [22] Udupa J., Murthy I.S.N., Syntactic approach to ECG rhythm analysis. IEEE Trans. Biomed. Eng., 1980, 27, pp. 370–375.