. B. Fig, 6 ? Ensemble complet de r` egles pour exper6

J. Aaron, C. Carlisle, M. Carskadon, T. Meyer, N. S. Hill et al., Environmental noise as a cause of sleep disruption in an intermediate respiratory care unit, Sleep, vol.19, issue.9, pp.707-710, 1996.

J. Adamec and R. Et-adamec, ECG Holter, 2000.
DOI : 10.1007/978-0-387-78187-7

V. Afonso, W. Tompkins, T. Nguyen, and L. Et-shen, ECG beat detection using filter banks, IEEE Transactions on Biomedical Engineering, vol.46, issue.2, pp.192-202, 1999.
DOI : 10.1109/10.740882

P. Beaufils, Recommandations de la société francaise de cardiologie pour la prise en charge des urgences cardiologiques, Archives des maladies du coeur et des vaisseaux, vol.92, issue.3, pp.337-344, 1999.

R. Bellazzi, C. Siviero, M. Stefanelli, and G. D. Et-nicolao, Adaptive controllers for intelligent monitoring, Artificial Intelligence in Medicine, vol.7, issue.6, pp.515-540, 1995.
DOI : 10.1016/0933-3657(95)00025-X

D. Benitez, P. Gaydecki, A. Zaidi, and A. Fitzpatrick, The use of the Hilbert transform in ECG signal analysis, Computers in Biology and Medicine, vol.31, issue.5, pp.399-406, 2001.
DOI : 10.1016/S0010-4825(01)00009-9

P. Bertier and J. Et-bouroche, L'analyse en composantes principales, pp.109-119, 1977.

L. Biot, L. Holzapfel, G. Becq, C. Melot, and P. Et-baconnier, Do we need a systematic activation of alarm soundings for blood pressure monitoring for the safety of ICU patients?, Journal of Critical Care, vol.18, issue.4, pp.212-216, 2003.
DOI : 10.1016/j.jcrc.2003.10.004

URL : https://hal.archives-ouvertes.fr/hal-00348269

C. Blitt, Monitoring in the Critical Care Unit, chapitre A philosophy of monitoring, pp.3-8, 1990.

I. Bratko, I. Mozeti?, and N. Et-lavra?, KARDIO : a study in deep and qualitative knowledge for expert systems, 1989.

M. Burke and M. Et-nasor, Wavelet based analysis and characterization of the ECG signal, Journal of Medical Engineering & Technology, vol.25, issue.2, pp.47-55, 2004.
DOI : 10.1080/0309190031000121532

D. Calvelo, M. Chambrin, D. Pomorski, and P. Et-ravaux, Towards symbolization using data-driven extraction of local trends for ICU monitoring, Artificial Intelligence in Medicine, vol.19, issue.3, pp.203-223, 2000.
DOI : 10.1016/S0933-3657(00)00046-4

URL : https://hal.archives-ouvertes.fr/hal-01509669

G. Carrault, M. Cordier, R. Quiniou, M. Garreau, J. Bellanger et al., A Model-Based Approach for Learning to Identify Cardiac Arrhythmias, Dans Artificial Intelligence in Medicine and Medical Decision Making (AIMDM', vol.1620, pp.165-174, 1999.
DOI : 10.1007/3-540-48720-4_18

G. Carrault, M. Cordier, R. Quiniou, and F. Wang, Temporal abstraction and inductive logic programming for arrhythmia recognition from electrocardiograms, Artificial Intelligence in Medicine, vol.28, issue.3, pp.231-263, 2003.
DOI : 10.1016/S0933-3657(03)00066-6

URL : https://hal.archives-ouvertes.fr/inserm-00134396

N. Carver and V. Et-lesser, A new framework for sensor interpretation : planning to resolve source of uncertainty, 9th National Conference on Artificial Intelligence (AAAI-91), pp.724-731, 1991.

S. Cauvin, M. Cordier, C. Dousson, P. Laborie, F. Lévy et al., The ALARM research group, monitoring and alarm interpretation in industrial environments, pp.3-4139, 1998.

M. Chambrin, Alarms in the intensive care unit : how can the number of false alarms be reduced ? Critical Care, pp.184-188, 2001.

I. Christov, Real time electrocardiogram QRS detection using combined adaptive threshold, Biomedical Engineering Online, vol.3, issue.28, pp.1-9, 2004.

R. Clouard, A. Elmoataz, and M. Et-revenu, Une modélisation explicite et opérationnelle de la connaissance de traitement d'images, 11 e ´ edition du congrès Reconnaissance des Formes et Intelligence Artificielle, pp.65-74, 1998.

V. Clément, Raisonnements cognitifs appliqués au pilotage d'algorithmes de traitement d'images, Thèse de doctorat, 1990.

V. Clément and M. Et-thonnat, A knowledge-based approach to integration of image procedures processing, Computer Vision Graphic and Image Processing (CVGIP) : Image Understanding, pp.166-184, 1993.

E. Coiera, Intelligent monitoring and control of dynamic physiological systems, Artificial Intelligence in Medicine, vol.5, issue.1, pp.1-8, 1993.
DOI : 10.1016/0933-3657(93)90002-K

M. Cordier and C. Et-dousson, Alarm driven monitoring based on chronicles, pp.286-291, 2000.

A. Cropp, L. Woods, D. Raney, and D. Et-bredle, Name That Tone, Chest, vol.105, issue.4, pp.1217-1220, 1994.
DOI : 10.1378/chest.105.4.1217

M. Crubézy, Pilotage de programmes pour le traitement d'images médicales, Thèse de doctorat, 1999.

P. Dalle and P. Et-dejean, Planification en traitement d'images : Approche basée sur les données, pp.75-84, 1998.

I. Daskalov and I. Et-christov, Electrocardiogram signal preprocessing for automatic detection of QRS boundaries, Medical Engineering & Physics, vol.21, issue.1, pp.37-44, 1999.
DOI : 10.1016/S1350-4533(99)00016-8

I. Daubechies, Orthonormal bases of compactly supported wavelets, Communications on Pure and Applied Mathematics, pp.909-996, 1988.

B. Dawant, S. Uckun, E. Manders, and D. Et-lindstrom, The SIMON project: model-based signal acquisition, analysis, and interpretation in intelligent patient monitoring, IEEE Engineering in Medicine and Biology Magazine, vol.12, issue.4, pp.82-91, 1993.
DOI : 10.1109/51.248170

R. Dechter, I. Meiri, and J. Et-pearl, Temporal constraint networks, Artificial Intelligence, vol.49, issue.1-3, pp.61-95, 1991.
DOI : 10.1016/0004-3702(91)90006-6

M. Dojat and L. Et-chittaro, Using a general theory of time and change in patient monitoring : experiment and evaluation, Computers in Biology and Medecine, vol.27, issue.5, pp.435-452, 1997.
URL : https://hal.archives-ouvertes.fr/inserm-00402432

M. Dojat, F. Pachet, Z. Guessoum, D. Touchard, A. Harf et al., N??oGanesh: a working system for the automated control of assisted ventilation in ICUs, Artificial Intelligence in Medicine, vol.11, issue.2, pp.97-117, 1997.
DOI : 10.1016/S0933-3657(97)00025-0

M. Dojat and C. Et-sayettat, Realistic model for temporal reasoning in real-time patient monitoring, Applied Artificial Intelligence, vol.10, issue.2, pp.121-143, 1996.
DOI : 10.1080/088395196118623

I. Dotsinsky and T. Et-stoyanov, Ventricular beat detection in single channel electrocardiograms, Biomedical Engineering Online, vol.3, issue.1, 2004.

C. Dousson, Suivi d'´ evolutions et reconnaissance de chroniques, Thèse de doctorat, 1994.

F. Duchêne, C. Garbay, and V. Et-rialle, Apprentissage non supervisé de motifs temporels, multidimensionnels et hétérogènes. applicationàapplication`applicationà la télésurveillance médicale, 7e conférence francophone sur l'apprentissage automatique, pp.181-182, 2005.

W. Einthoven, Le t??l??cardiogramme, Archives Internationales de Physiologie, vol.4, pp.132-164, 1906.
DOI : 10.1007/978-94-010-1301-7_9

J. Fernández, M. Harris, and C. Et-meyer, Combining Algorithms in Automatic Detection of R-peaks in ECG Signals, 18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05), pp.297-302, 2005.
DOI : 10.1109/CBMS.2005.43

J. Fraden and M. Et-neuman, QRS wave detection, Medical & Biological Engineering & Computing, vol.12, issue.2, pp.125-132, 1980.
DOI : 10.1007/BF02443287

G. M. Friesen, T. C. Jannett, M. A. Jadallah, S. L. Yates, S. R. Quint et al., A comparison of the noise sensitivity of nine QRS detection algorithms, IEEE Transactions on Biomedical Engineering, vol.37, issue.1, pp.85-98, 1990.
DOI : 10.1109/10.43620

E. Fromont, Apprentissage multisource par programmation logique inductive : applicationàapplication`applicationà la caractérisation d'arythmies cardiaques, Thèse, 2005.

E. Fromont, M. Cordier, R. Quiniou, and A. Et-hernández, KARDIO and CALICOT : a comparison of two cardiac arrhythmia classifiers, 9th Conference on Artificial Intelligence in Medicine Qualitative and Model-based Reasoning in Biomedicine, 2003.
URL : https://hal.archives-ouvertes.fr/inria-00001049

E. Fromont and F. Et-portet, Pilotage d'un système de monitoring cardiaque multisource, e MAnifestation des JEunes Cherchers du domaine des Sciences et Technologies de l'Information et de la Communication (MAJECSTIC 2005), 2005.

E. Fromont, R. Quiniou, and M. Et-cordier, Learning rules from multisource data for cardiac monitoring, 10th Conference on Artificial Intelligence in Medicine, pp.484-493, 2005.
URL : https://hal.archives-ouvertes.fr/inria-00000184

C. Fuchsberger, J. Hunter, and P. Et-mccue, Testing Asbru Guidelines and Protocols for Neonatal Intensive Care, 10th Conference on Artificial Intelligence in Medicine, pp.101-110, 2005.
DOI : 10.1007/11527770_14

J. Gamper and W. Et-nejdl, Abstract temporal diagnosis in medical domains, Artificial Intelligence in Medicine, vol.10, issue.3, pp.209-234, 1997.
DOI : 10.1016/S0933-3657(97)00393-X

H. Gerapetritis and J. M. Et-pelissier, The critical success index and warning strategy, 17th Conference on Probablity and Statistics in the Atmospheric Sciences, 2004.

E. Goldberger, A simple, indifferent, electrocardiographic electrode of zero potential and a technique of obtaining augmented, unipolar, extremity leads, American Heart Journal, vol.23, issue.4, pp.483-492, 1942.
DOI : 10.1016/S0002-8703(42)90293-X

F. Gritzali, Towards a generalized scheme for QRS detection in ECG waveforms, Signal Processing, vol.15, issue.2, pp.183-192, 1988.
DOI : 10.1016/0165-1684(88)90069-2

M. Guertin, Abductive inference of events : diagnosing cardiac arrhythmias, 9th Florida Artificial Intelligence Research Symposium, pp.106-111, 1996.

T. Guyet, C. Garbay, and M. Et-dojat, Human/Computer Interaction to Learn Scenarios from ICU Multivariate Time Series, 10th Conference on Artificial Intelligence in Medicine, pp.424-428, 2005.
DOI : 10.1007/11527770_57

URL : https://hal.archives-ouvertes.fr/inserm-00519870

I. Haimowitz and I. Et-kohane, Managing temporal worlds for medical trend diagnosis, Artificial Intelligence in Medicine, vol.8, issue.3, pp.299-321, 1996.
DOI : 10.1016/0933-3657(95)00037-2

B. Hayes-roth, K. Pfelger, P. Lalanda, P. Morignot, and M. Et-balabanovic, A domain-specific software architecture for adaptive intelligent systems, IEEE Transactions on Software Engineering, vol.21, issue.4, pp.288-301, 1995.
DOI : 10.1109/32.385968

A. Hernández, Fusion de signaux et de modèles pour la caractérisation d'arythmies cardiaques Thèse de doctorat, Université de Rennes 1. prétation des battements cardiaques, 14 e ´ edition du congrès Reconnaissance de Formes et Intelligence Artificielle, pp.447-456, 2000.

A. Hernández, G. Carrault, F. Mora, L. Thoraval, G. Passariello et al., Multisensor fusion for atrial and ventricular activity detection in coronary care monitoring, IEEE Transactions on Biomedical Engineering, vol.46, issue.10, pp.461186-1190, 1999.
DOI : 10.1109/10.790494

D. Hess, Noninvasive monitoring in respiratory care -present, past, and future : an overview, Respiratory Care, vol.35, pp.482-498, 1990.

S. Hoeksel, J. Jansen, J. Blom, and J. Et-schreuder, Detection of dicrotic notch in arterial pressure signals, Journal of Clinical Monitoring, vol.13, issue.5, pp.309-316, 1997.
DOI : 10.1023/A:1007414906294

N. Holter, New Method for Heart Studies, Annals of Noninvasive Electrocardiology, vol.196, issue.4, pp.1214-1229, 1961.
DOI : 10.1111/j.1542-474X.1998.tb00046.x

W. Horn, AI in medicine on its way from knowledge-intensive to data-intensive systems, Artificial Intelligence in Medicine, vol.23, issue.1, pp.5-12, 2001.
DOI : 10.1016/S0933-3657(01)00072-0

J. Hunter and I. Kirby, Ticker : A qualitative model of the electrical system of the heart, Research and Development in Expert Systems XII, pp.293-307, 1995.

J. Jenkins and S. Et-caswell, Detection algorithms in implantable cardioverter defibrillators, Proceedings of the IEEE, pp.428-445, 1996.
DOI : 10.1109/5.486745

S. Kadambe, R. Murray, and F. Et-boudreaux-bartels, Wavelet transformbased QRS complex detector, IEEE Transactions on Biomedical Engineering, issue.7, pp.47838-848, 1999.

G. Karsai and J. Et-sztipanovits, A model-based approach to self-adaptive software, IEEE Intelligent Systems, vol.14, issue.3, pp.46-53, 1999.
DOI : 10.1109/5254.769884

A. Keith and M. Et-flack, The auriculo-ventricular bundle of the human heart, Lancet, vol.2, pp.359-364, 1906.

S. Kent, A conducting path between the right auricle and exterior wall of the right ventricle in the heart of the mammal, Journal of Physiology, vol.48, p.57, 1914.

F. Klassner, V. Lesser, and H. Et-nawab, The IPUS blackboard architecture as a framework for computational auditory scene analysis. Computational Auditory Scene Analysis, pp.105-114, 1998.

B. Kohler, C. Hennig, and R. Et-orglmeister, The principles of software QRS detection, IEEE Engineering in Medicine and Biology Magazine, vol.21, issue.1, pp.42-57, 2002.
DOI : 10.1109/51.993193

A. Koulouris, G. Papakonstantinou, and P. Et-tsanakas, A Decentralized Multichannel Length Transformation Algorithm and Its Parallel Implementation for Real-Time ECG Monitoring, Computers and Biomedical Research, vol.33, issue.4, pp.227-244, 2000.
DOI : 10.1006/cbmr.2000.1544

C. Lake, Clinical Monitoring, 1990.

J. Larsson and B. Hayes-roth, Guardian: intelligent autonomous agent for medical monitoring and diagnosis, IEEE Intelligent Systems, vol.13, issue.1, pp.58-64, 1998.
DOI : 10.1109/5254.653225

S. T. Lawless, Crying wolf, Critical Care Medicine, vol.22, issue.6, pp.981-985, 1994.
DOI : 10.1097/00003246-199406000-00017

L. Certen, G. Soulas, T. Carrault, G. Et-le-pichon, and J. , SIMBAD : Intelligent ECG monitoring system (a real time software implementation), 8th International IMEKO Conference on Measurement in Clinical Medicine Biomedical measurement and instrumentation & 12th International Symposium on Biomedical Engineering, pp.3-11, 1998.

L. Moulec and F. , ´ Etude et réalisation d'un modèle qualitatif profond de l'activité activitéélectrique du coeur pour un système de monitoring intelligent en unité de soins intensifs pour coronariens, Thèse de doctorat, 1991.

V. Lesser, H. Nawab, I. Gallastegi, and F. Et-klassner, IPUS: an architecture for the integrated processing and understanding of signals, 11th National Conference on Artificial Intelligence (AAAI-93), pp.249-255, 1993.
DOI : 10.1016/0004-3702(94)00033-W

V. Lesser, H. Nawab, and F. Et-klassner, IPUS: an architecture for the integrated processing and understanding of signals, Artificial Intelligence, vol.77, issue.1, 1993.
DOI : 10.1016/0004-3702(94)00033-W

V. Lesser, S. Nawab, and F. Et-klassner, IPUS: an architecture for the integrated processing and understanding of signals, Artificial Intelligence, vol.77, issue.1, pp.129-171, 1995.
DOI : 10.1016/0004-3702(94)00033-W

C. Li, C. Zheng, and C. Tai, Detection of ECG characterictic points using wavelet transforms, IEEE Transactions on Biomedical Engineering, vol.42, pp.21-28, 1995.

K. Liszka, M. Mackin, M. Lichter, D. York, D. Pillai et al., Keeping a Beat on the Heart, IEEE Pervasive Computing, vol.3, issue.4, pp.42-49, 2004.
DOI : 10.1109/MPRV.2004.10

A. Lowe, R. Jones, and M. Et-harrison, The graphical presentation of decision support information in an intelligent anaesthesia monitor, Artificial Intelligence in Medicine, vol.22, issue.2, pp.173-191, 2001.
DOI : 10.1016/S0933-3657(00)00106-8

S. Mabry, T. Schneringer, T. Etters, and N. Et-edwards, Intelligent agents for patient monitoring and diagnostics, Proceedings of the 2003 ACM symposium on Applied computing , SAC '03, pp.257-262, 2003.
DOI : 10.1145/952532.952585

J. Mackay and G. Et-mensah, The Atlas of Heart Disease and Stroke, 2004.

S. Mallat, A Wavelet Tour of Signal Processing, 1999.

R. Mark and G. Et-moody, MIT-BIH arrhythmia data base directory, 1988.

H. Marsh, Monitoring in the Critical Care Unit, chapitre Monitoring in Anesthesia and Critical Care Medicine, pp.815-827, 1990.

M. Matousek and E. Et-posner, Purkyne's (Purkinje's) muscle fibres in the heart., Heart, vol.31, issue.6, pp.718-721, 1969.
DOI : 10.1136/hrt.31.6.718

S. Meystre, The current state of telemonitoring : a comment on the literature. Telemedicine and e-Health, pp.63-69, 2005.

S. Miksch, W. Horn, C. Popow, and F. Et-paky, Utilizing temporal data abstraction for data validation and therapy planning for artificially ventilated newborn infants, Artificial Intelligence in Medicine, vol.8, issue.6, pp.543-576, 1996.
DOI : 10.1016/S0933-3657(96)00355-7

S. Moisan, Une plate-forme pour une programmation par composants de syst` emesàemes`emesà base de connaissances. HabilitationàHabilitation`Habilitationà diriger les recherches, 1998.

S. Moisan and M. Et-thonnat, Knowledge-based systems for program supervision. Dans 1st International Workshop on Knowledge Based systems for the (re)Use of Program Libraries, pp.4-8, 1995.

S. Moisan, R. Vincent, and M. Et-thonnat, Program supervision : from knowledge modeling to dedicated engines, 1997.
URL : https://hal.archives-ouvertes.fr/inria-00073365

S. Moisan and D. Et-ziébelin, Résolution deprobì emes en pilotage de programmes, 12 e ´ edition du congrès Reconnaissance des Formes et Intelligence Artificielle, 2000.

G. Moody, W. Muldrow, and R. Mark, A noise stress test for arrhythmia detectors, Computers in Cardiology, vol.11, pp.381-384, 1984.

A. Mora, G. Passariello, G. Carrault, and J. Et-le-pichon, Intelligent patient monitoring and management systems: a review, IEEE Engineering in Medicine and Biology Magazine, vol.12, issue.4, pp.23-33, 1993.
DOI : 10.1109/51.248164

V. Moret-bonillo, A. Alonso-betanzos, E. G. Martín, M. C. Canosa, and B. G. Et-berdiñas, The PATRICIA project: a semantic-based methodology for intelligent monitoring in the ICU, IEEE Engineering in Medicine and Biology Magazine, vol.12, issue.4, pp.59-68, 1993.
DOI : 10.1109/51.248168

V. Moret-bonillo, M. Cabrero-canosa, and E. Et-hernandez-pereira, Integration of data, information and knowledge in intelligent patient monitoring, Expert Systems with Applications, vol.15, issue.2, pp.155-163, 1998.
DOI : 10.1016/S0957-4174(98)00020-7

K. Morik, M. Imboff, P. Brockhausen, T. Joachims, and U. Et-gather, Knowledge discovery and knowledge validation in intensive care, Artificial Intelligence in Medicine, vol.19, issue.3, pp.225-249, 2000.
DOI : 10.1016/S0933-3657(00)00047-6

V. Nagin and S. Et-selishchev, Implementation of algorithms for identification of QRS-complexes in real time ECG systems, Biomedical Engineering, vol.35, issue.6, pp.304-309, 2001.
DOI : 10.1023/A:1014626021370

M. Nygårds, L. Et, and . Sörnmo, A QRS delineation algorithm with low sensitivity to noise and morphology changes, Cardiology, pp.347-350, 1981.

M. Okada, A digital filter for the QRS complex detection, IEEE Transactions on Biomedical Engineering BME, vol.26, pp.700-703, 1979.

J. Bibliographie-pan and W. J. Et-tompkins, A real-time QRS detection algorithm, IEEE Transactions on Biomedical Engineering, vol.32, issue.3, pp.230-236, 1985.

D. J. Pierson, Principles and Practice of Intensive Care Monitoring, chapitre Goals and indications for monitoring, pp.33-44, 1998.

R. Poli, S. Cagnoni, and G. Valli, Genetic design of optimum linear and nonlinear QRS detectors, IEEE Transactions on Biomedical Engineering, vol.42, issue.11, pp.42-1137, 1995.
DOI : 10.1109/10.469381

C. Popow, W. Horn, B. Rami, and E. Et-schober, VIE-DIAB: A Support Program for Telemedical Glycaemic Control, pp.350-354, 2003.
DOI : 10.1007/978-3-540-39907-0_48

F. Portet and G. Et-carrault, Piloting real-time QRS detection algorithms in variable contexts, 3rd European Medical and Biological Engineering Conference (EMBEC'05), 2005.
URL : https://hal.archives-ouvertes.fr/inria-00001101

F. Portet, G. Carrault, M. Cordier, and R. Et-quiniou, Pilotage en ligne d'algorithmes de traitement du signal guidé par le contexte courant, 7e Rencontres des Jeunes Chercheurs en Intelligence Artificielle (RJCIA'05), pp.1-14, 2005.

F. Portet, G. Carrault, M. Cordier, and R. Et-quiniou, Signal processing algorithms in a cardiac monitoring context, First Doctoral Consortium of the 10th Conference on Artificial Intelligence in Medicine Aber- deen, 2005.
URL : https://hal.archives-ouvertes.fr/inria-00001098

F. Portet, G. Carrault, M. Cordier, and R. Et-quiniou, Pilotage d algorithmes pour un diagnostic médical robuste en cardiologie, 2006.

F. Portet, A. Hernández, and G. Et-carrault, Evaluation of real-time QRS detection algorithms in variable contexts, Medical & Biological Engineering & Computing, vol.15, issue.3, pp.381-387, 2005.
DOI : 10.1007/BF02345816

URL : https://hal.archives-ouvertes.fr/inria-00001102

P. Purkinje, Mikroskopisch-neurologische beobachtungen, Archiv für Anatomie, pp.281-295, 1845.

R. Quiniou, M. Cordier, G. Carrault, and F. Wang, Application of ILP to Cardiac Arrhythmia Characterization for Chronicle Recognition, Lecture Notes in Computer Science, vol.2157, pp.220-227, 2001.
DOI : 10.1007/3-540-44797-0_18

P. Rubel, J. Fayn, L. Sinon-chautemps, H. Atoui, M. Ohlsson et al., New paradigms in telemedicine : ambient intelligence, wearable, pervasive and personalized, Studies in Health Technology and Informatics, vol.108, pp.123-132, 2004.

A. Ruha, S. Sallinen, and S. Et-nissilä, A real-time microprocessor QRS detector system with a 1-ms timing accuracy for the measurement of ambulatory HRV, IEEE Transactions on Biomedical Engineering, vol.44, issue.3, pp.44159-167, 1997.
DOI : 10.1109/10.554762

L. Senhadji, Approche multirésolution pour l'analyse des signaux non stationnaires, Thèse de doctorat, 1993.

L. Senhadji, G. Carrault, J. Bellanger, and G. Et-passariello, Comparing wavelet transforms for recognizing cardiac patterns, IEEE Engineering in Medicine and Biology Magazine, vol.14, issue.2, pp.167-173, 1995.
DOI : 10.1109/51.376755

URL : https://hal.archives-ouvertes.fr/inserm-00152896

Y. Shahar and M. Et-musen, R??SUM??: A Temporal-Abstraction System for Patient Monitoring, Computers and Biomedical Research, vol.26, issue.3, pp.255-273, 1993.
DOI : 10.1006/cbmr.1993.1018

S. Sharshar, L. Allart, and M. Et-chambrin, A New Approach to the Abstraction of Monitoring Data in Intensive Care, 10th Conference on Artificial intelligence in medicine, pp.13-22, 2005.
DOI : 10.1007/11527770_3

C. Shekhar, P. Burlina, and S. Et-moisan, Design of self-tuning IU systems, Defense Advanced Research Projects Agency (DARPA) : Image Understanding Workshop, pp.529-536, 1997.

C. Shekhar, S. Moisan, and M. Et-thonnat, Towards an intelligent problem-solving environment for signal processing, Mathematics and Computers in Simulation, vol.36, issue.4-6, pp.347-359, 1994.
DOI : 10.1016/0378-4754(94)90069-8

E. Shortliffe, Computer-Based Medical Consultations : MYCIN, 1976.

R. Silipo and C. Et-marchesi, Artificial neural networks for automatic ECG analysis, IEEE Transactions on Signal Processing, vol.46, issue.5, pp.1417-1425, 1998.
DOI : 10.1109/78.668803

P. Siregar, M. Chahine, F. Lemoulec, and P. Et-le-beux, An interactive qualitative model in cardiology, Computers and Biomedical Research, vol.28, issue.6, pp.443-478, 1995.
DOI : 10.1016/S0010-4809(85)71029-4

P. Siregar, J. Coatrieux, and P. Et-le-beux, KISS : Knowledge based interactive signal monitoring system, 1989.

T. Soulas, Une architecture de monitoring intelligent pour le domaine médical (Approche méthodologique -Application en cardiologie), Thèse de doctorat, 2001.
DOI : 10.1016/s1297-9562(01)90025-7

T. Soulas, G. Le-certen, J. Le-pichon, and G. Et-carrault, Algorithm switching in real time monitoring, Symposium on Electronics and Telecommunications (ETC), pp.145-149, 1998.

L. Sterling and E. Shapiro, The art of PROLOG. Logic Programming, 1986.

M. Stridh and L. Et-sörnmo, Spatiotemporal QRST cancellation techniques for analysis of atrial fibrillation, IEEE Transactions on Biomedical Engineering, vol.48, issue.1, pp.105-111, 2001.
DOI : 10.1109/10.900266

B. Sukuvaara, T. Sydänmaa, M. Nieminen, H. Heikelä, A. Et-koski et al., Object oriented implementation of an architecture for patient monitoring, IEEE Engineering in Medicine and Biology Magazine, vol.12, issue.4, pp.69-81, 1993.
DOI : 10.1109/51.248169

Y. Sun, K. Chan, and S. Krishnan, ECG signal conditioning by morphological filtering, Computers in Biology and Medicine, vol.32, issue.6, pp.465-479, 2002.
DOI : 10.1016/S0010-4825(02)00034-3

S. Suppappola and Y. Et-sun, Nonlinear transforms of ECG signals for digital QRS detection: a quantitative analysis, IEEE Transactions on Biomedical Engineering, vol.41, issue.4, pp.397-400, 1994.
DOI : 10.1109/10.284971

J. Sztipanovits, G. Karsai, and T. Et-bapty, Self-adaptive software for signal processing, Communications of the ACM, vol.41, issue.5, pp.55-65, 1998.
DOI : 10.1145/274946.274958

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.97.9630

S. Tawara, Das reizleitungsysem des säugetierherzens : eine anatomishhistologische studië uber das atrioventrikularbündel und die purkinjeschen fäden, 1906.

S. Tawara, The conduction System of the Mammalian Heart : an anatomicohistological study of the atrioventricular bundle and the purkinje fibers. imperial college press, 2000.
DOI : 10.1142/p099

M. Thonnat and S. Et-moisan, Knowledge-based systems for program supervision, Knowledge Based (re)Use of Program Libraries (KBUP'95), pp.3-8, 1995.

L. Thoraval, G. Carrault, J. Schleich, R. Summers, M. Van-de-velde et al., Data fusion of electrophysiological and haemodynamic signals for ventricular rhythm tracking, IEEE Engineering in Medicine and Biology Magazine, vol.16, issue.6, pp.48-55, 1997.
DOI : 10.1109/51.637117

C. Tsien and J. Et-falcker, Poor prognosis for existing monitors in the intensive care unit, Critical Care Medicine, vol.25, issue.4, pp.614-619, 1997.
DOI : 10.1097/00003246-199704000-00010

S. Uckun, Intelligent system in patient monitoring and therapy management, International Journal of Clinical Monitoring and Computing, vol.4, issue.1, 1993.
DOI : 10.1007/BF01139876

C. Vilhelm, Conception et développement d'un outils de traitement de connaissances, 1998.

C. Vilhelm, A. Jaborska, M. Chambrin, and P. Et-ravaux, A software architecture for a medical data acquisition, report and interpretation system in intensive care unit, Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1996.
DOI : 10.1109/IEMBS.1996.656825

C. Vilhelm, P. Ravaux, D. Calvelo, A. Jaborska, M. Chambrin et al., Think!: A unified numerical???symbolic knowledge representation scheme and reasoning system, Artificial Intelligence, vol.116, issue.1-2, pp.67-85, 2000.
DOI : 10.1016/S0004-3702(99)00095-8

G. Wagner, W. Stork, and K. Et-müller-glaser, MODEL-BASED EVALUATION OK DIFFERENT QRS DETECTION ALGORITHMS FOR USE IN MOBILE SYSTEMS, Biomedizinische Technik/Biomedical Engineering, vol.48, issue.s1, pp.210-211, 2003.
DOI : 10.1515/bmte.2003.48.s1.210

F. Wang, Abstraction temporelle de signal ECG, apprentissage inductif de contraintes temporelles et reconnaissance des arythmies cardiaques, Thèse, 2002.

F. Wang, R. Quiniou, G. Carrault, and M. Et-cordier, Learning Structural Knowledge from the ECG, 2nd International Symposium on Medical Data Analysis, pp.288-294, 2001.
DOI : 10.1007/3-540-45497-7_44

R. Watrous and G. Et-towell, A patient-adaptive neural network ECG patient monitoring algorithm, Computers in Cardiology 1995, 1995.
DOI : 10.1109/CIC.1995.482614

O. Wieben, V. Afonso, and W. Et-tompkins, Classification of premature ventricular complexes using filter bank features, induction of decision trees and a fuzzy rule-based system, Medical & Biological Engineering & Computing, vol.8, issue.5, pp.560-565, 1999.
DOI : 10.1007/BF02513349

F. Wilson, F. Johnston, A. Mcleod, and P. Et-barker, Electrocardiograms that represent the potential variations of a single electrode, American Heart Journal, vol.9, issue.4, pp.447-471, 1934.
DOI : 10.1016/S0002-8703(34)90093-4

F. Wilson, F. Johnston, F. Rosenbaum, H. Erlanger, C. Kossmann et al., The precordial electrocardiogram, American Heart Journal, vol.27, issue.1, pp.19-85, 1944.
DOI : 10.1016/S0002-8703(44)90603-4

A. Wrzesniowski and P. Et-augustyniak, Adaptive channels weighting for the QRS detection in long-term electrocardiograms, 6th International Conference SYMBIOSIS 2001, pp.27-32, 2001.

A. Zoubir and B. Et-boashash, The bootstrap and its application in signal processing, IEEE Signal Processing Magazine, vol.15, issue.1, pp.56-76, 1998.
DOI : 10.1109/79.647043