In this paper, the authors propose an on-line signal processing algorithm which is capable to significantly improve the performance. After characterizing the dynamic behavior of the sensor system, a ...properly designed deconvolution filter is used to reduce response time and signal noise. They also provide an example of this algorithm for a novel electrochemical sensor for the measurement of the anesthetic agent propofol in exhaled air. For this application, the acceleration is prerequisite for the measurement chain to be of practical use in a clinical setting. The goals, to establish measurement dynamics to record the physiologic parameter and to reduce non-physiological disturbances, were achieved with additional reserves. As an example, they present propofol monitoring in breath of one patient in order to demonstrate the performance of the introduced algorithm in a real clinical application. They proved that the electrochemical sensor, associated with the provided algorithm, is capable for real-time monitoring in a clinical setting.
Identifying and comparing different steady states is an important task for clinical decision making. Data from unequal sources, comprising diverse patient status information, have to be interpreted. ...In order to compare results an expressive representation is the key. In this contribution we suggest a criterion to calculate a context-sensitive value based on variance analysis and discuss its advantages and limitations referring to a clinical data example obtained during anesthesia. Different drug plasma target levels of the anesthetic propofol were preset to reach and maintain clinically desirable steady state conditions with target controlled infusion (TCI). At the same time systolic blood pressure was monitored, depth of anesthesia was recorded using the bispectral index (BIS) and propofol plasma concentrations were determined in venous blood samples. The presented analysis of variance (ANOVA) is used to quantify how accurately steady states can be monitored and compared using the three methods of measurement.
The anesthetic agent propofol is applied intravenously and different groups demonstrated that it is detectable in breathing gas. To quantify the propofol concentration in breathing gas (c breath ) ...might be a promising feedback for anesthesiologist and for potential closed loop control, yet there is no online measurement in standard clinical practice. Since the physiological relevance of the propofol concentration in breath is not entirely known it may be adverse to control the infusion with c breath as target variable. In order to control the concentration at the plasma site (c plasma ) or even at the effect site (c effect ) in the brain mathematical models can be used to describe the dependencies between c breath and c plasma or c effect . This contribution presents the pharmacokinetic modeling of the transition from blood to alveolar gas concentration of propofol. For characterization a model described by a gas blood partition coefficient and one time constant or an equivalent one compartment system, respectively, is taken into account. Clinical data obtained in a study with 17 patients are used for fitting. During anesthesia breathing gas was monitored continuously with an electrochemical sensor and venous blood samples were taken at given times. The use of the mentioned model structure leads to a simple and adequate characterization. A data conditioning in form of a model based interpolation was performed prior to the identification process. The identified parameters are comparable to results of other research works.