Automating the Calibration of a Neonatal Condition Monitoring System
نویسندگان
چکیده
Condition monitoring of premature babies in intensive care can be carried out using a Factorial Switching Linear Dynamical System (FSLDS) [15]. A crucial part of training the FSLDS is the manual calibration stage, where an interval of normality must be identified for each baby that is monitored. In this paper we replace this manual step by using a classifier to predict whether an interval is normal or not. We show that the monitoring results obtained using automated calibration are almost as good as those using manual calibration.
منابع مشابه
Auto-Calibration for Neonatal Condition Monitoring
This project describes our approach for automating the calibration stage needed by the Factorial Switching Linear Dynamical System (FSLDS) for neonatal condition monitoring. Using observations collected by the monitoring equipment, the FSLDS proposed by Prof Christopher Williams and Dr John Quinn [22] is highly successful in inferring the probability distributions of both physiological and arti...
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