| Abstract | There is currently no universally accepted approach to weaning patients from mechanical ventilation, but
there is clearly a feeling within the medical community that it may be possible to formulate the weaning
process algorithmically in some manner. Fuzzy logic seems suited this task because of the way it so
naturally represents the subjective human notions employed in much of medical decision-making. The
purpose of the present study was to develop a fuzzy logic algorithm for controlling pressure support
ventilation in patients in the intensive care unit, utilizing measurements of heart rate, tidal volume, breathing
frequency, and arterial oxygen saturation. In this report we describe the fuzzy logic algorithm, and
demonstrate its use retrospectively in 13 patients with severe chronic obstructive pulmonary disease, by
comparing the decisions made by the algorithm with what actually transpired. The fuzzy logic
recommendations agreed with the status quo to within 2 cm H(2)O an average of 76% of the time, and to
within 4 cm H(2)O an average of 88% of the time (although in most of these instances no medical
decisions were taken as to whether or not to change the level of ventilatory support). We also compared
the predictions of our algorithm with those cases in which changes in pressure support level were actually
made by an attending physician, and found that the physicians tended to reduce the support level
somewhat more aggressively than the algorithm did. We conclude that our fuzzy algorithm has the potential
to control the level of pressure support ventilation from ongoing measurements of a patient's vital signs. |