TY - JOUR
T1 - Development of an expert system for haemodynamic monitoring
T2 - Computerized symbolization of on-line monitoring data
AU - Koski, Erkki
AU - Mäkivirta, Aki
AU - Sukuvaara, Tommi
AU - Kari, Aarno
N1 - Project code: SAI6003
Project code: SAI0007
PY - 1992
Y1 - 1992
N2 - The development of intelligent alarm systems for intensive care benefits from the transformation of data from a quantitative to a qualitative mode. We constructed a computerized algorithm for the symbolization of on-line monitoring data of heart rate, systemic arterial, pulmonary arterial and central venous pressures, as well as central and peripheral temperatures. We tested the ability of the algorithm to symbolize the levels of the parameters and to detect significant long-term trends in ten adult patients admitted to the intensive care unit after cardiac surgery. The estimations of an experienced clinician were taken as the ‘gold standard’. The symbolization of the levels of the monitored parameters was in agreement with the clinician in 99.4% of the estimations. The algorithm detected 93.0% of the trends correctly and also estimated their reliability. The clinician considered its estimations to be accurate in 96.2% of cases. On the other hand, the clinician considered unreliable 2.4% of all the trends detected and classified as reliable by the algorithm. The computerized algorithm for the symbolization of real-time monitoring data performed efficiently enough for its further use in expert systems for intelligent monitoring.
AB - The development of intelligent alarm systems for intensive care benefits from the transformation of data from a quantitative to a qualitative mode. We constructed a computerized algorithm for the symbolization of on-line monitoring data of heart rate, systemic arterial, pulmonary arterial and central venous pressures, as well as central and peripheral temperatures. We tested the ability of the algorithm to symbolize the levels of the parameters and to detect significant long-term trends in ten adult patients admitted to the intensive care unit after cardiac surgery. The estimations of an experienced clinician were taken as the ‘gold standard’. The symbolization of the levels of the monitored parameters was in agreement with the clinician in 99.4% of the estimations. The algorithm detected 93.0% of the trends correctly and also estimated their reliability. The clinician considered its estimations to be accurate in 96.2% of cases. On the other hand, the clinician considered unreliable 2.4% of all the trends detected and classified as reliable by the algorithm. The computerized algorithm for the symbolization of real-time monitoring data performed efficiently enough for its further use in expert systems for intelligent monitoring.
U2 - 10.1007%2FBF01739130
DO - 10.1007%2FBF01739130
M3 - Article
SN - 1387-1307
VL - 8
SP - 289
EP - 293
JO - Journal of Clinical Monitoring and Computing
JF - Journal of Clinical Monitoring and Computing
IS - 4
ER -