SIGNAL PROCESSING/AUTOMATION FOR CARDIAC OUTPUT MONITOR

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Thermal dilution is by far the most common method of measuring cardiac output. Over one million thermodilution pulmonary artery catheters are used each year in the U.S. We have applied artificial neural networks to improve the accuracy of the thermal dilution cardiac output measurement and allow using small injectate volumes (2 ml). We propose to build an automated system using a modified syringe pump and a solid state injectate cooler to automatically measure cardiac output once every minute. Recently introduced devices automate this measurement and provide continuous measurement, however, these devices require special catheters costing $195.00 per patient and require long averaging periods (10 min.). Our system would achieve the same accuracy and real-time data using a standard catheter costing $40.00 per patient. We have tested the technique in five animals and have found the system capable of making cardiac output measurements using only 2 ml injectate volumes. The small volume technique gave measurements with accuracy similar to those obtained using the standard of 10 ml iced injectate over wide range of cardiac outputs. We plan to build a proto-type automated system and test it in 10 animals. Less than 12% errors in animal tests using the automated system will be considered success.