The Science Journal of the American Association for Respiratory Care

2011 OPEN FORUM Abstracts


Christina Long, Joseph Orr, Lara M. Brewer; Anesthesiology, Bioengineering Laboratory, University of Utah, Salt Lake City, UT

Introduction: Capnometers are currently tested for minimum performance standards using tanks containing fixed concentrations of CO2 flowing at constant rates. These testing protocols do not test for a capnometers's ability to accurately calculate clinical parameters such as respiratory rate and end-tidal CO2. Ideal standards should test capnometers with changing flow rates and frequencies of respiration, as well as with capnograms that have complex shapes and trends. This paper presents a capnometry simulator that has the ability to overcome the limitations of current testing protocols by reproducing clinically recognized time-based capnograms. Methods: Our simulator consists of: 1) 100% CO2 and O2 gas sources, 2) a simulator enclosure, 3) a reference capnometer, and 4) a computer with stored capnograms. The concept of the simulator is to continuously change the flow rate of CO2 being injected into a constant flow of O2, in order to create varying CO2 partial pressures over time that mimic capnograms. The CO2 flow rate is computer controlled through a variable orifice solenoid valve that outputs higher flow rates for higher input currents. Its response is non-linear and requires calibration before use. Once the CO2 is injected into the O2 stream, the mixed gas is diverted to the reference capnometer, which is used to calibrate the CO2 valve and measure the performance of the simulator. The reference capnometer used in this study was the NICO2 (Phillips Respironics, Wallingford, CT). Five capnograms were used to simulate different CO2 levels, respiratory rates, and waveform shapes and trends. These files include waveforms from intensive care unit (ICU), operating room (OR), new born, pediatric, and sedated adult patients. Results: The average statistics for five minute simulations were root mean squared error (RMSE) = 1.99 mmHg, normalized root mean squared error (NRMSE) = 3.77%, mean absolute error (MAE) = 1.40 mmHg, and R2 = 0.989. Conclusion: The results show that our simulator can accurately reproduce time-based capnograms from clinical settings. With further research and optimization, this device can potentially standardize and improve testing methods used for capnometry. As part of future work, additional capnometers will be tested and compared to the one used in this study.
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