C. Annexe, Récapitulatif des informations disponibles sur les systèmes utilisés Fig. 66: Les paramètres obtenus à partir du signal de pression à partir du capnogramme : la concentration ou pression partielle du

. Partir-de-la-photopléthysmographie-de-pouls, Le moniteur de SpO2 fournit également la saturation de l'hémoglobine en oxygène calculée à partir d'une technique de spectrophotométrie d'absorption

. Sortiej8, DB9broches male (voir schéma de connexion, tous les pins sont connectés)

J. Annexe, A. Silvent, M. Dojat, and C. Et-garbay, Multi-level temporal abstraction for medical scenario construction. Special Issue of the International Journal of Signal Processing and Adaptive Control. A paraître Workshops internationaux Silvent A Data, information and knowledge for medical scenario construction, Proceedings on Intelligent Data Analysis in Medicine and Pharmacology, 2003.

A. Silvent, C. Garbay, P. Carry, and M. Dojat, Data abstraction for medical construction scenario, Knowledge Data from Temporal and Spatial Data (TASDA'02), 2002.

A. Conférences-nationales-avec-publication-dans-un-livre-silvent, C. Garbay, C. P. Dojat, and M. , Abstraction de données pour la construction de scénarios médicaux, Extraction et Gestion des Connaissances (EGC'2003) Hermès-Lavoisier, pp.22-24, 2003.

J. Bibliographie-]-allen, Maintaing knowledge about temporal intervals, Comm. ACM, vol.26, issue.11, p.832843, 1983.

J. Allen, Towards a general theory of action and time, Artificial Intelligence, vol.23, issue.2, p.123154, 1984.
DOI : 10.1016/0004-3702(84)90008-0

. Bauer, Analysis of High Dimensional Data from Intensive Care Medicine, Proceedings in Computational Statistics, p.185190, 1998.
DOI : 10.1007/978-3-662-01131-7_19

G. Becq, Gestion des alarmes d'oxymétrie de pouls en unités de soins intensifs :une analyse multiparamétrée, 2000.

. Bellazzi, Quality assessment od dialysis services through intelligent data analysis and temporal data mining, Working notes workshop on Knowledge Discovery on Temporal and Spatial data, ECAI 2002, pp.3-9, 2002.

. Bellazzi, Temporal data mining for the quality assessment of hemodialysis services, Artificial Intelligence in Medicine, vol.34, issue.1, 2005.
DOI : 10.1016/j.artmed.2004.07.010

. Bellazzi, Quality assessment of hemodyalisis services through temporal data mining, 9 th conference on Articial Intelligence in Medicine in Europe, AIME2003 LNCS 2780, p.1120, 2003.

. Bellazzi, Mining biomedical time series by combinig structural analysis and temporal abstractions, Journal of American medical informatics association, vol.5, p.160164, 1998.

L. Biot, Evaluation d'un monitorage de la mécanique respiratoire en réanimation adulte, Thèse de médecine, 1998.

. Biot, Clinical evaluation of alarm eciency in intensive care, Ann. Fr. Anesth. Reanim, vol.19, issue.6, p.45966, 2000.

I. Bloch, Fusion d'informations en traitement du signal et des images, 2003.

. Bloch, . Hunter, I. Bloch, and A. Hunter, Fusion: General concepts and characteristics, International Journal of Intelligent Systems, vol.9, issue.10, p.1611071134, 2001.
DOI : 10.1002/int.1052

. Bloch, . Maître, I. Bloch, and H. Maître, Fusion de données en traitement d'images : modèles d'informations et décisions, Traitement du Signal, issue.6, p.11435446, 1994.

. Burns, Implementation of an institutional program to improve clinical and nancial outcomes of mechanically ventilated patients : One-year outcomes and lessons learned, Critical Care Medicine, issue.12, p.3127522763, 2003.

D. Calvelo-arosaros, Apprentissage de modèles de la dynamique pour l'aide à la décision en monitorage clinique, Thèse de doctorat, 1999.

. Carrault, A Model-Based Approach for Learning to Identify Cardiac Arrhythmias, AIMDM'99, p.165174, 1999.
DOI : 10.1007/3-540-48720-4_18

. Carrault, Temporal abstraction and inductive logic programming for arrhythmia recognition from electrocardiograms, Artificial Intelligence in Medicine, vol.28, issue.3, p.231263, 2003.
DOI : 10.1016/S0933-3657(03)00066-6
URL : https://hal.archives-ouvertes.fr/inserm-00134396

E. Bijaoui, P. Carry, S. Charbonnier, M. Dojat, C. Garbay et al., Osscar : A collaborative project for intelligent patient monitoring in intensive care and anesthesia, Proceedings on Intelligent Data Analysis in Medicine and Pharmacology, 2003.

. Chambrin, Multicentric study of monitoring alarms in the adult intensice care unit (icu) : a descriptive analysis, Intensive care medicine, issue.12, pp.251360-1366, 1999.

J. Charlet, L'ingénierie des connaissances : une science, un enseignement ? In Ingénierie des connaissances, plate-forme AFIA, p.233252, 2001.

. Chiu, Probabilistic discovery of time series motifs, Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '03, 2003.
DOI : 10.1145/956750.956808

. Cios, K. Moore-]-cios, and G. Moore, Uniqueness of medical data mining, Artificial Intelligence in Medicine, vol.26, issue.1-2, p.124, 2002.
DOI : 10.1016/S0933-3657(02)00049-0

. Cios, A knowledge discovery approach to diagnosing myocardial perfusion, IEEE Engineering in Medicine and Biology Magazine, vol.19, issue.4, p.1725, 2000.
DOI : 10.1109/51.853478

W. Clancey, Heuristic classification, Artificial Intelligence, vol.27, issue.3, pp.289-350, 1985.
DOI : 10.1016/0004-3702(85)90016-5

. Clerq, Approaches for creating computer-interpretable guidelines that facilitate decision support, Articial Intelligence in Medicine, vol.31, p.127, 2004.

. Cortés, Dai-depur : an environmenttal decision support system for control and supervision of municipal waste water treatment plants, p.15, 2002.

D. Decoste, Dynamic across-time measurement interpretation, Artificial Intelligence, vol.51, issue.1-3, 1991.
DOI : 10.1016/0004-3702(91)90113-X

M. Dojat, Contribution à la représentation d'expertises médicales dynamiques : application en réanimation médicale, Thèse de doctorat, 1994.

B. Dojat, M. Dojat, and L. Brochard, Knowledge-based systems for automatic ventilatory management, Respiratory Care Clinics of North America, vol.7, issue.3, 2001.
DOI : 10.1016/S1078-5337(05)70048-4
URL : https://hal.archives-ouvertes.fr/inserm-00402401

. Dojat, Clinical Evaluation of a Computer-controlled Pressure Support Mode, American Journal of Respiratory and Critical Care Medicine, vol.161, issue.4, p.11611166, 2000.
DOI : 10.1164/ajrccm.161.4.9904064
URL : https://hal.archives-ouvertes.fr/inserm-00402420

. Dojat, N??oGanesh: a working system for the automated control of assisted ventilation in ICUs, Artificial Intelligence in Medicine, vol.11, issue.2, p.97117, 1997.
DOI : 10.1016/S0933-3657(97)00025-0

. Dojat, Scenario recognition for temporal reasoning in medical domains, Artificial Intelligence in Medicine, vol.14, issue.1-2, p.139155, 1998.
DOI : 10.1016/S0933-3657(98)00020-7
URL : https://hal.archives-ouvertes.fr/inserm-00402424

C. Dousson, Extending and unifying chronicle representation with event counters, Proceedings of the 15, 2002.

. Dousson, C. Duong-]-dousson, and T. V. Duong, Découverte de chroniques avec contraintes temporelles à partir de journaux d'alarmes pour la supervision de réseaux de télécommunications, Actes de la première conférence d'apprentissage (CAP'99), p.1724, 1999.

P. Dubois, D. Dubois, and H. Prade, La problématique scientique du traitement de l'information. Information-Interaction-Intelligence, 2001.

M. Duftshmid, G. Duftshmid, and S. Miksch, Knowledged-based verication of clinical guidelines by detection of anomalies, Articial Intelligence in Medicine, vol.22, p.2341, 2001.

E. Ely, Eect on the duration of mechanical ventilation of the identifying patients capable of breathing spontaneously, The New England Journal of Medicine, vol.335, p.18641869, 1996.

. Ely, The prognostic significance of passing a daily screen of weaning parameters, 587. on Knowledge Engineering : Methods & Languages, p.581, 1999.
DOI : 10.1007/s001340050906

G. Miller, The marginal number seven, plus or minus two : some limits to our capacity for processing information, Psychol. Rev, vol.63, p.8197, 1956.

K. Morik, The Representation Race ??? Preprocessing for Handling Time Phenomena, 2000.
DOI : 10.1007/3-540-45164-1_2

. Morik, Combining statistical learning with a knowledge-based approach. a case study in intensive care monitoring, p.16, 1999.

. Morik, Knowledge discovery and knowledge validation in intensive care, Articial Intelligence in Medicine, vol.19, issue.3, p.225250, 2000.

A. Morris, COMPUTERIZED PROTOCOLS AND BEDSIDE DECISION SUPPORT, Critical Care Clinics, vol.15, issue.3, p.523545, 1999.
DOI : 10.1016/S0749-0704(05)70069-5

A. Morris, Rational use of computerized protocols in the intensive care unit, Critical Care, vol.5, p.249254, 2001.

A. Morris, Decision support and safety of clinical environments, Quality and Safety in Health Care, vol.11, issue.1, p.6975, 2002.
DOI : 10.1136/qhc.11.1.69

. Peleg, Glif3 : the evolution of a guideline representation format, Proceedings of the American Medical Informatics Association (AMIA) Annual Symposium, p.645649, 2000.

. Peleg, Comparing Computer-interpretable Guideline Models: A Case-study Approach, Journal of the American Medical Informatics Association, vol.10, issue.1, p.5268, 2003.
DOI : 10.1197/jamia.M1135

J. Pitrat, Métaconnaissance. Futur de l'intelligence articielle, 1990.

. Quaglini, Flexible guideline-based patient careow systems, Articial Intelligence in Medicine, vol.22, p.6580, 2001.

N. Ramaux, Supervision de systèmes dynamiques par reconnaissance de scénarios, Thèse de doctorat, 1998.

S. Roddick, J. Roddick, and M. Spiliopoulou, A survey of temporal knowledge discovery paradigms and methods, IEEE Transactions on Knowledge and Data Engineering, vol.14, issue.4, p.750767, 2002.
DOI : 10.1109/TKDE.2002.1019212

. Rodriguez-roda, A hybrid supervisory system to support wwtp operation : implementation and validation. Water science and technology, pp.4-5289297, 2002.

T. Russ, Use of data abstraction methods to simplify monitoring, Artificial Intelligence in Medicine, vol.7, issue.6, p.497514, 1995.
DOI : 10.1016/0933-3657(95)00024-8

. Seyfang, Combining diagnosis and treatment using asbru, International Journal of Medical Informatics, vol.68, issue.1-3, p.684957, 2002.
DOI : 10.1016/S1386-5056(02)00064-3

Y. Shahar, A knowledge-based method for temporal abstraction of clinical data, 1994.

Y. Shahar, A framework for knowledge-based temporal abstraction, Artificial Intelligence, vol.90, issue.1-2, p.79133, 1997.
DOI : 10.1016/S0004-3702(96)00025-2

. Shahar, . Cheng, Y. Shahar, and C. Cheng, Intelligent visualisation and exploration of time-oriented clinical data, Annual Hawaii International Conference on System Sciences (HICSS-32), 1999.

. Shahar, The Asgaard project: a task-specific framework for the application and critiquing of time-oriented clinical guidelines, Artificial Intelligence in Medicine, vol.14, issue.1-2, p.2951, 1998.
DOI : 10.1016/S0933-3657(98)00015-3

. Shi, Principles for measuring association rules, 2002.

Y. Shoham, Temporal logics in AI: Semantical and ontological considerations, Artificial Intelligence, vol.33, issue.1, p.89104, 1987.
DOI : 10.1016/0004-3702(87)90052-X

F. Steimann, Diagnostic monitoring of clinical time series, 1995.

F. Steimann, The interpretation of time-varying data with DiaMon-1, Artificial Intelligence in Medicine, vol.8, issue.4, p.343357, 1996.
DOI : 10.1016/0933-3657(95)00040-2

P. Szolovits, Uncertainty and decisions in medical informatics, Methods of Information in Medicine, vol.34, p.111121, 1995.

L. Travé-massuyès and R. Milne, Gas-turbine condition monitoring using qualitative model-based diagnosis, IEEE Expert : Intelligent systems and their applications, p.2231, 1997.
DOI : 10.1109/64.590070

C. Tsien, Trendnder : Automated detection of alarmable trends. PhD, Massachusetts institute of technology, 2000.

. Tsien, Multiple signal integration by decision tree induction to detect artifacts in the neonatal intensive care unit, Artificial Intelligence in Medicine, vol.19, issue.3, p.189202, 2000.
DOI : 10.1016/S0933-3657(00)00045-2

M. Tu, S. Tu, and M. Musen, A exible approach to guideline modeling, Proceedings of the AMIA Symp, p.420424, 1999.

A. Unwin, If you can't see the pattern, is it there ? In Exploratory worshop on pattern detection and discovery in data mining, LNCS 2447, p.6376, 2002.