CO2 and its influence on environmental and ecological processes focuses the attention of all current media. In the medical area, expired CO2 measurement with Capnography has gained acceptance for all patients needing clinical monitoring and supervision. But recent research works are showing the promises of CO2 as a diagnostic tool or therapeutic monitoring. In this case, measurement of expired CO2 in function of the expired volume, called Volumetric Capnography, has a theoretical better performance than the traditional time-based Capnography. When expired CO2 data are combined to arterial CO2 sampling, the clinician faces breath-by-breath curves, which give a bedside knowledge of the pulmonary ventilation and perfusion status of his patient. Pulmonary embolism is a particular application of Volumetric Capnography. This frequent and challenging disease is characterized by impaired relationships between the pulmonary ventilation and perfusion, going from deadspace to shunt. Volumetric Capnography deserves a careful attention in this area, since its combination with other clinical or biological signs could become part of a diagnostic procedure, either for the detection of the disease when capnographic parameters are clearly impaired, or for ruling out this diagnosis when Volumetric Capnography analysis is normal. In the same way, monitoring the efficacy of thrombolytic therapy when pulmonary embolism is massive is another particular interest for expired CO2 measurement. Physicians working in the Emergency Department demand performing devices for improving patient care. Such devices can be particularly adapted to daily practice if they can be used by the bedside, if they are non-invasive, safe, efficient, feasible, and applicable to non-intubated patients. Volumetric Capnography, which seems to answer those requirements, will certainly deserve growing attention and interest in the future as a direct application of pulmonary pathophysiology. Even if Volumetric Capnography is still at the frontier between clinical research and clinical practice, let us hope that the studies presented in this thesis will improve the clinical acceptance of this attractive technology.

Volumetric CO2 data from patients in anaesthesia delivery systems are sought after by physicians. The CO2 data obtained with the commonly used sidestream sampling technique are not considered adequate for volumetric CO2 estimation due to distortion and desynchrony with patient flow. The purpose of this thesis was to explore the possibility of using signal enhancing methods to the sidestream data to accurately estimate CO2 flow using a Flow-i anaesthesia delivery system. To evaluate sidestream performance, experimental data was acquired using a mainstream and a sidestream capnograph connected in series to a FRC test lung with known CO2 content, ventilated by a Flow-i anaesthesia machine. The data was then enhanced and analysed using signal processing methods including sigmoid modelling and neural networks. A Feed Forward Neural Network achieved results closest resembling the mainstream capnogram of the evaluated signal processing methods. The mainstream capnogram, considered the benchmark, produced large internal scattering and approximately 25 % offset from actual CO2 flow while using the inherent patient flow data produced by the Flow-i anaesthesia system. When using patient flow data from a Servo-i ventilator, the resulting CO2 flow estimates were drastically improved, producing estimates within 10 % error. This thesis concludes that there are several potential processing methods of the sidestream data to approximate the mainstream signal, however the patient flow of the Flow-i system are a suspected source of error in the CO2 flow estimation.