An expert system for monitor alarm integration

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dc.contributor.authorOberli, C
dc.contributor.authorUrzua, J
dc.contributor.authorSaez, C
dc.contributor.authorGuarini, M
dc.contributor.authorCipriano, A
dc.contributor.authorGarayar, B
dc.contributor.authorLema, G
dc.contributor.authorCanessa, R
dc.contributor.authorSacco, C
dc.contributor.authorIrarrazaval, M
dc.date.accessioned2025-01-21T01:32:17Z
dc.date.available2025-01-21T01:32:17Z
dc.date.issued1999
dc.description.abstractObjective. Intensive care and operating room monitors generate data that are not fully utilized. False alarms are so frequent that attending personnel tends to disconnect them. We developed an expert system that could select and validate alarms by integration of seven vital signs monitored on-line from cardiac surgical patients. Methods. The system uses fuzzy logic and is able to work under incomplete or noisy information conditions. Patient status is inferred every 2 seconds from the analysis and integration of the variables and a uni ed alarm message is displayed on the screen. The proposed structure was implemented on a personal computer for simultaneous automatic surveillance of up to 9 patients. The system was compared with standard monitors (Space-Labs (TM) PC2), using their default alarm settings. Twenty patients undergoing cardiac surgery were studied, while we ran our system and the standard monitor simultaneously. The number of alarms triggered by each system and their accuracy and relevance were compared. Two expert observers (one physician, one engineer) ascertained each alarm reported by each system as true or false. Results. Seventy-five percent of the alarms reported by the standard monitors were false, while less than 1% of those reported by the expert system were false. Sensitivity of the standard monitors was 79% and sensitivity of the expert system was 92%. Positive predictive value was 31% for the standard monitors and 97% for the expert system. Conclusions. Integration of information from several sources improved the reliability of alarms and markedly decreased the frequency of false alarms. Fuzzy logic may become a powerful tool for integration of physiological data.
dc.fuente.origenWOS
dc.identifier.issn1387-1307
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/97237
dc.identifier.wosidWOS:000081047600005
dc.issue.numero1
dc.language.isoen
dc.pagina.final35
dc.pagina.inicio29
dc.revistaJournal of clinical monitoring and computing
dc.rightsacceso restringido
dc.subjectmonitoring
dc.subjectintelligent monitoring
dc.subjectcritical care
dc.subjectalarm integration
dc.subjectfuzzy logic
dc.subjectexpert systems
dc.subjectfalse alarms
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleAn expert system for monitor alarm integration
dc.typeartículo
dc.volumen15
sipa.indexWOS
sipa.trazabilidadWOS;2025-01-12
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