Abstract
Traditionally, patients in intensive care are connected to a bedside monitor which, using various invasive and non-invasive transducers, monitors the patient’s vital functions such as blood pressure, heart rate, saturation of oxygen and any number of other parameters to address the particular problems of the patient. The bedside monitor uses independent limit-alarms to detect alarm conditions for each of these parameters independently. The upper and lower limits of these limit-alarms determine the bounds of acceptability of the vital function outside of which an alarm sounds. In the current generation of bedside monitors the upper and lower limits must be set by the nurse, or the factory defaults are used. The performance of a system based on these limit-alarms is poor due to a number of reasons which will be discussed in this chapter.
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Dodd, N. (2000). Patient Monitoring Using an Artificial Neural Network. In: Lisboa, P.J.G., Ifeachor, E.C., Szczepaniak, P.S. (eds) Artificial Neural Networks in Biomedicine. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-0487-2_10
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DOI: https://doi.org/10.1007/978-1-4471-0487-2_10
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