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26, 10, pp. 879-887.

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  • - Cardona JFR (2004): ,Reduccion en tiempo real de perturbaciones en señales de ECG empleando la transformada Wavelet sobre DSP’, Universidad Nacional de Colombia, Facultad de Ingenieria y Arquitectura, Departamento de Electricidad, Electronica y Computacion, Manizales, Colombia, pp. 1-108.

  • - Rodrigo Varejão Andreão (2004): Segmentation de battements ECG par approche markovienne: Application à la détection d'ischémies. Tese de Doutorado (PhD), Institut National des Télécommunications, INT, France.

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  • - Exarchos TP, Papaloukas C, Fotiadis DI (2005); ‘A Novel Methodology for Myocardial Ischaemia Diagnosis Using Association Rules’, European Medical & Biological Engineering Conference, IEEE, Prague, Czech Republic, Editor(s):IEEE, November, CD-ROM Article No 1545.

  • -Chudácek V, Hanuliak M, Lhotská L (2005): ‘Clustering of heartbeats for automated ECG Holter analysis’, 3rd European Medical & Biological Engineering Conference, IEEE, Prague, Czech Republic, Editor(s):IEEE, November, CD-ROM Article No 2113.

  • -Jekova I, Krasteva V (2005): ‘Fast Algorithm for Vectorcardiogram and Interbeat Intervals Analysis: Application for Premature Ventricular Contractions Classification’, Bioautomation, 3, pp. 82-93.

  • - Carlson J, Havmöller R, Herreros A, Platonov P, Johansson R, Olsson B (2005): ‘Can orthogonal lead indicators of propensity to atrial fibrillation be accurately assessed from the 12-lead ECG?’, Oxford Journal of Europace, 7, No s2, pp. s39-s48.

  • - Carlson J (2005); ‘Exploration of supraventricular conduction with respect to atrial fibrillation’, Methodological aspects on selected techniques, Doctoral Dissertation, Faculty of Medicine, Lund, University, Sweden.

    http://luur.lub.lu.se/luur?func=downloadFile&fileOId=545701

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    http://www.hst.aau.dk/~vval04/Papers/report_master.pdf

    1. - Exarchos TP, Papaloukas C, Fotiadis DI, Michalis LK (2006): ‘An associated rule mining-based methodology for automated detection of ischemic ECG beats’, IEEE Transactions on Biomedical Engineering, 53, (8), pp. 1531-1540.

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    4. -Chudáček V, Georgoulas G, Stylios C, Staviar M, Hanuliak M, Lhotská L (2006): Comparison of methods for premature ventricular beat detection’, Information Technology Applications in Biomedicine, ITAB 2006, 26-28 October, Ioannina, Greece, pp. 1-4.

    http://medlab.cs.uoi.gr/itab2006/proceedings/ECG%20&%20Bioimpedance/130.pdf

    1. -Jager F (2006): ‘Introduction to feature extraction’, Chapter 9 in: : Advanced Methods for ECG Analysis, Eds. G. D. Clifford, F. Azuaje and P. E. McSharryArtech House, London.

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    3. - Fotiadis D, Likas A, Michalis L, Papaloukas C (2006): ‘Electrocardiogram (ECG): Automated Diagnosis’, Wiley Encyclopedia of Biomedical Engineering, Copyright © 2006 John Wiley & Sons, Inc., 4056 pages.

    4. - Exarchos TP, Papaloukas C, Fotiadis D (2006): ‘A decision tree based approach for the identification of ischaemic beats in Ecg recordings’, pp. 312-319, In: Mathematical Methods in Scattering Theory and Biomedical Engineering, Eds: Fotiadis D, Massalas C, © World Scientific, 440 pages.

    5. - Khawaja A (2006): ‘Automatic ECG analysis using principal component analysis and wavelet transformation’, Disertation Doktor-Engenieurs, Universität Frediriciana Karlsruhe, Karlsruhe Transaction on Biomedical Engineering, 3, pp. 1-246,

    http://www.uvka.de/univerlag/volltexte/2007/227/pdf/Khawaja_Antoun.pdf

    1. - Tito Coutinho Melco (2006): ‘Estudo do eletrocardiograma sobre uma abordagem matemática’, Thesis, Departamento de Engenharia Mecatrônica e de Sistemas Mecânicos da Universidade de São Paulo, 100 pages. http://subversion.assembla.com/svn/enfasebccfrb/Material%20De%20pesquisa/TITOCOUTINHOMELCO.pdf

    2. - Михов Г (2007): ‘Електронни устройства, системи и методи за обектно-ориентирана обработка на сигнали за потискане на смущения и идентифициране на полезни компоненти’, хабилитационен труд за присъждане на научното звание ст.н.с. І ст.

    3. - Kannathal N, Acharya UR, Ng EYK, Min LC, Suri JS, Spaan JAE (2007): ‘Data Fusion of Multimodal Cardiovascular Signals’, In: Advances in Cardiac Signal Processing, Eds: Acharya UR, Suri J, Spaan JAE, Krishnan SM, Springer Berlin Heidelberg, chapter 6, pp. 167-186.

    4. -- Wang Hengdi, Zhu Jianmin, Lin Lifeng, Liang Li: (2007) ‘Lorenz plot and its application in automatic diagnoses of atrial fibrillation ECG signals’, Journal of Biomedical Engineering, 24, (2), pp. 449-452,

    http://www.wanfangdata.com.cn/qikan/periodical.Articles/swyxgcx/swyx2007/070

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    1. - Melco TC, Moscato LA (2007): ‘Estudo do Eletrocardiograma sobre uma Abordagem Matemática’, Boletins Técnicos, ISSN 1517-3526 BT/PMR/070, Departamento de Engenharia Mecatrônica e de Sistemas Mecânicos da Universidade de São Paulo, pp. 1-29,

    http://www.pmr.poli.usp.br/pmr/bt/BTPMR0707.pdf

    1. - Exarchos TP, Tsipouras MG, Exarchos CP, Papaloukas C, Fotiadis DI, Michalis LK (2007): A methodology for the automated creation of fuzzy expert systems for ischaemic and arrhythmic beat classification based on a set of rules obtained by a decision tree’, Arificial Intelligence in Medicine, 40, (3), pp. 187-200.

    2. -ﺴﻟا ﺐﻨﻳز ، ﻬﻣ ،ﻲﻜﺧﺎﻛ ﻲﻠﻛﻮﺗ نﺎﺴ يﺪﻬﺸﻣ ﻲﺒﺟر ﺐﻴﺒﺣ ، ﻲﭽﻧﻮﺗﻮﺗ (2007) QRS آﺷﻜﺎرﺳﺎز ﺑﻬﻴﻨﻪ ﺟﻬﺖ ﻃﺮاﺣﻲ PSO و GA اﻟﮕﻮرﻳﺘﻢ ﺗﺮﻛﻴﺒﻲ ECG در ﺳﻴﮕﻨﺎل. First Joint Congress on Fuzzy and Intelligent Systems, Ferdowsi University of Mashhad, Iran, 29-31 August,

    http://confbank.um.ac.ir/modules/conf_display/isfs2007/article/i857.pdf

    1. - Havmoller R, Carlson J, Holmqvist F, Herreros A, Meurling CJ, Olsson B, Platonov P (2007): ‘Age-related changes in P wave morphology in healthy subjects’, BMC Cardiovascular Disorders, 7, 22,  pp. 1-27,

    http://www.biomedcentral.com/content/pdf/1471-2261-7-22.pdf

    1. - Naydenov S, Donova T, Matveev M, Gegova A, Popdimitrova N, Zlateva G, Vladimirova D (2007): ‘High-frequency electrocardiography: Optimizing the diagnosis of the acute myocardial infarct with ST-elevatio’, AIP Conference Proceedings, 899, pp. 819.

    2. - Krasteva V, Iliev I (2007): ‘Automatic analysis and visualization of multilead long-term ECG recordings’, Electronics ET’2007, book 23, pp. 67-72.

    3. - Mohebbi M, Moghadam HA (2007): ‘Real-time ischemic beat classification using backpropagation neural network’, IEEE 15th Signal Processing and Communications Applications Conference, 11-13 June, Eskisehir, Turkey, 4 .pages

    4. - Mohebbi M, Moghadam HA (2007): ‘An Algorithm for Automated Detection of Ischemic ECG Beats Using Support Vector Machines’, IEEE 15th Signal Processing and Communications Applications Conference, 11-13 June, Eskisehir, Turkey, 4 pages

    5. - Mohebbi M, Moghadam HA Teshnehlab, M (2007): ‘An Automated System for On-line Monitoring and Detection of ST Changes in ECG Signal’, IEEE 15th Signal Processing and Communications Applications Conference, 11-13 June, Eskisehir, Turkey, 4 pages

    6. - Silva H, Gamboa H, Fred A (2007): ’One lead ECG based personal identification with feature subspace ensembles’, book chapter, pp. 770-783, In: Machine learning and data mining in pattern recognition, © Springer Berlin/Heidelberg.

    7. - Tsipouras MG, Voglis C, Fotiadis DI (2007): ‘A framework for fuzzy expert system creation – application to cardiovascular diseases’, IEEE Trans. Biomed. Engng, 54, (11), pp. 2089-2105.

    8. - Chudáček V, Petrík M, Georgoulas G, Čepek M., Lhotská L, Stylios C (2007) Comparison of seven approaches for holter ECG clustering and classification. 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Lyon, France, 22-26 Aug., pp. 3844 –3847.

    9. - Čepek M, Chudáček V, Petrík M, Georgoulas G, Stylios C, Lhotská L (2007): ‘Comparison of inductive modeling method to other classification methods for Holter ECG’, 2nd International Workshop on Inductive Modelling, Prague, September 23-26, pp.229-241.

     http://www.gmdh.net/articles/iwim/IWIM_33.pdf.

    1. - Shantha SKR., Sadavisam V (2007): ‘Wavelet-based base line wandering removal and R peak and QRS complex detection’, International Journal of Wavelets, Multiresolution and Information Processing, 5, (6), pp. 927-939.

    2. - Martínez A, Rossi E (2007): ‘Desarrollo e implementación de un simulator de señales electrocardiográficas’, Proceedings of XVI Congreso Argentino de Bioingenieria SABI 2007, V Jornadas de Ingenieria Clinica, 26-28 September, pp. 1-10.

    3. - Petrik M, Chudacek V, Lhotska L (2007): ‘Generalization of rule-based decision tree to fuzzy intervals for ECG-beat clustering’, IEEE Workshop on Machine Learning for Signal Processing, Thessaloniki, Greece, 27-29 August, pp. 205-210.

    4. - Wang Hengdi, Zhu Jianmin, Liang Li, Shen Bo (2007): ‘A simple and accurate algorithm for identifying the R waves’, Sheng Wu Yi Xue Gong Cheng Xue Za Zhi, 24, (5), pp.1019-1022.

    5. - Kumari RSS, Sadasivam V (2007): Wavelet-based base line wandering removal and R peak and QRS complex detection’, International Journal of Wavelets, Multiresolution and Information Processing, 5, (6), pp. 927 - 939.

    6. - Dobrev D, Neycheva T, Mudrov N (2008): ‘Bootstrapped two-electrode biosignal amplifier’, Med. Biolog. Eng. Comput., 46, pp. 613-619.

    http://www.springerlink.com/content/h768696g72636r73/

    1. - Илиев И (2008): ‘Ограничаване на мрежовите смущения при телеметрично регистриране на биомедицински сигнали’, Национолно конференция с международно участие”Eлектроника 2008”, 29-30 май, София, рр. 107-110.

    2. - Dori G, Bitterman H (2008): ‘ECG variability contour - a reference for evaluating the significance of amplitude ECG changes in two states’, Physiol Meas 29, (8), pp. 989-997.

    3. - Albright CM, Quinn AT, Berberian G, Cabreriz SE, Garofalo CA, Weinberg AD, Dizo JM, Spotnitz HM (2008): ‘ Measurement of QRS duration for biventricular pacing optimization’, Journal of the American Society for ArtificialInternal Organs, 54, (4), pp. 335-341.

    4. - Malik M, Hnatkova K, Ford J, Madge D (2008): ‘Near-thorough QT study as part of a first-in-man study’, Journal of Clinical Pharmacology, Pharmacokinetics and Pharmacodynamics, doi:10.1177/0091270008323261, pp. 1146-1157.

    5. - Malik M, Hnatkova K, Schmidt A, Smetana P (2008): ‘Accurately measured and properly heart-rate corrected QTc intervals show little day-time variability’, Heart Rhythm, 5, (10), pp. 1424-1431.

    6. - Kumari SS, Sadasivam V (2008): ‘QRS complex detection using double density discrete wavelet transform’, Biomedical Engineering: Applications, Basis and Communications, 20, (2), pp. 65-73.

    7. - Smrdel A, Jager F (2008): ‘An algorithm to estimate the ST segment level in 24-hour ambulatory ECG records’, Comp. in Card., 35, pp.

    http://cinc.mit.edu/cgi-bin/preprint-2008?number=P94-4

    1. - Malik M, Hnatkova K, Sisakova M, Schmidt G (2008): ‘Subject-specific heart rate dependency of electrocardiographic QT, PQ, and QRS intervals’, Journal of Electrocardiology, 41, (6), pp. 491-497.

    2. - Malik M, Hnatkova K, Novotny T, Schmidt G (2008): ‘Subject-specific profiles of QT/RR hysteresis’, Am J Physiol - Heart & Circulatory Physiol, 295, pp. H2356 - H2363.

    3. - Edilson Delgado Trejos (2008): ‘Generación y Extracción/Selección de Características en la Detección Automática de Isquemia y Deficiencias Valvulares sobre Registros de la Actividad Cardíaca’, Tesis Doctor en Ingeniería, Departamento de Ingeniería Eléctrica, Electrónica y Computación, Universidad Nacional de Colombia Sede Manizales, 257 pages, http://www.digital.unal.edu.co/dspace/bitstream/10245/1479/1/edilsondelgadotrejos.2008.pdf.pdf

    4. - Μαρκο Τσιπουρας (2008): ‘Ευφυεις μεθοδοι διαγνωσης καρδιαγγειακων παθησεων’, Tμημα Παηροφορικης, Department of Computer Science, University of Ioannina, Greece, 265 pages. (Tsipouras M. (2008):’Intelligent methods for cardiovascular diseases diagnosis’, PhD Thesis, Department of Computer Science, University of Ioannina, Greece, 292 pages; N45. http://charon.cs.uoi.gr/~tech_report/hci/publications/phd_2008_01.pdf.)

    5. - Hnatkova K, Smetana P, Toman O, Bauer A, Schmidt G, Malik M (2009): ‘Systematic comparisons of electrocardiographic morphology increase the precision of QT interval measurement’, PACE - Pacing and Clinical Electrophysiology 32, (1), pp. 119-130.

    6. - Chudacek V, Petrik M, Huptych M, Lhotska L (2008): ‘Fuzzy rule based decision tree classification of ECG Holter beats’, pp. 242-253. In: Advanced Topics in Scattering and Biomedical Engineering, Eds: Charalambopoulos A, Fotiadis DI, Polyzos D., 389 pages.

    7. - Salim Graja (2008): ‘Segmentation et classification de l’onde P d’un électrocardiogramme: détection d’un risque de fibrillation auriculaire’, Docteur de l’ENST Bretagne, l’École Nationale Supérieure des Télécommunications de Bretagne.

    8. - Manis G, Alexandridi A, Nikolopoulos S, Davos K (2009): ‘The effect of white noise and false peak detection on HRV analysis’, 6 pages, http://users.ntua.gr/nikiplos/hrv_noise_cr.pdf

    9. - Salim Graja (2008): ‘Segmentation et classification de l'onde P d'un électrocardiogramme : détection d'un risque de fibrillation auriculaire’, Docteur de l'ENST Bretagne, l'École Nationale d'Ingenieurs de Tunis, 237 pages,

    http://portail.telecom-bretagne.eu/publi/public/download.jsp?id_publication=5301

    1. - Dori G, Gershinsky M, Ben-Haim S, Lewis BS, Bitterman H (2009): ‘Evaluating rest ECG amplitude changes using the ECG variability contour method’, Computers in Cardiology, 36, pp. 837-840.

    2. - Malik M, Hnatkova K, Schmidt A, Smetana P (2009): ‘Electrocardiographic QTc changes due to Moxifloxacin infusion’, J. of Clin. Pharmacology, 49, (6), pp. 674-683.

    3. - Chudácek V, Georgoulas G, Lhotská L, Stylios C, Petrík M, Cepek M (2009:)’ Examining cross-database global training to evaluate five different methods for ventricular beat classification’, Phys. Meas., 30, pp. 661-677.

    4. - Табаков С (2009): ‘Pитъмен анализ на сърдечната дейност, приложим в автономни системи за мониториране’, Дисертация д-р”, ТУ. – София, 111 стр.

    5. - Havmoller R, Carlson J, Holmqvist F, Olsson B, Platonov P (2009): ‘Evolution of P-wave morphology in healthy individuals: A 3-year follow-up study’, Annals of Noninvasive Electrocardiology, 14, (3), pp. 226-233.

    6. - Hassan HH, Abraham TM, Joseph KP (2009): ‘Fuzzy clustered probabilistic and multi layered feed forward neural networks for electrocardiogram arrhythmia classification’, Online Journal of Medical Systems, pp 1-10, http://www.springerlink.com/content/1q6l172464437300/fulltext.html

    7. - Author MA (2009): ‘Fast Computation and Applications to Ischemic Detection from Electrocardiograms of the Dilated, Discrete Hermite Transform’, 35th Annual Northeast Bioengineering Conference, Cambridge, MA, 3-5 April, pp. 189-190.

    8. - Filomena E, Aldonate J, Rubén A, Spinelli E (2009): ‘Revisión sobre nuevas tendencias en la adquisición de biopotenciales’, XVII Congreso Argentino de Bioingenieria, VI Jornadas de Ingenieria Clinica
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