A knowledge- and model-based system for automated weaning from mechanical ventilation: technical description and first clinical application

Abstract

To describe the principles and the first clinical application of a novel prototype automated weaning system called Evita Weaning System (EWS). EWS allows an automated control of all ventilator settings in pressure controlled and pressure support mode with the aim of decreasing the respiratory load of mechanical ventilation. Respiratory load takes inspired fraction of oxygen, positive end-expiratory pressure, pressure amplitude and spontaneous breathing activity into account. Spontaneous breathing activity is assessed by the number of controlled breaths needed to maintain a predefined respiratory rate. EWS was implemented as a knowledge- and model-based system that autonomously and remotely controlled a mechanical ventilator (Evita 4, Dräger Medical, Lübeck, Germany). In a selected case study (n = 19 patients), ventilator settings chosen by the responsible physician were compared with the settings 10 min after the start of EWS and at the end of the study session. Neither unsafe ventilator settings nor failure of the system occurred. All patients were successfully transferred from controlled ventilation to assisted spontaneous breathing in a mean time of 37 ± 17 min (± SD). Early settings applied by the EWS did not significantly differ from the initial settings, except for the fraction of oxygen in inspired gas. During the later course, EWS significantly modified most of the ventilator settings and reduced the imposed respiratory load. A novel prototype automated weaning system was successfully developed. The first clinical application of EWS revealed that its operation was stable, safe ventilator settings were defined and the respiratory load of mechanical ventilation was decreased.

Classification of Sputum Sounds Using Artificial Neural Network and Wavelet Transform

“…The vast majority of patients with mechanical ventilation in ICU are lack of the ability of self-expectoration for the establishment of artificial airway and coma position 1 , so they depend on artificial secretion clearance. Sputum deposition in the airway can cause dyspnea and pulmonary infection 2 , 3 . As a type of common complications of mechanically ventilated patients, the incidence of ventilator associated pneumonia (VAP) is as high as 68%, and the mortality is as high as 50-70% 4 .…”

The European Society for Computing and Technology in Anaesthesia and Intensive Care (ESCTAIC): A special issue of full papers (Erlangen meeting 2011) and conference abstracts (Timisoara, meeting 2014)

“…These reflect the activities of ESCTAIC meeting participants spanning a wide range of interests from clinical workflow [4], data representation and management [5], application of data and models in decision support [6], to detailed analysis of individual continuous measurements [7]. Each of these papers illustrates novel technological contribution in the fields of anaesthesia and intensive care.…”

“…Four full papers [4][5][6][7] were accepted following peer review for publication in this issue. These reflect the activities of ESCTAIC meeting participants spanning a wide range of interests from clinical workflow [4], data representation and management [5], application of data and models in decision support [6], to detailed analysis of individual continuous measurements [7].…”

“…The paper is largely technical, describing the platform for integrating the Medical Logic Modules (MLMs) of the Arden syntax, but also discusses the current status of clinical implementation with MLM's having been implemented for data-driven monitoring of laboratory values, and user driven decision support and these currently being applied an average of 442 times per day. Schädler et al [6] present a novel system for controlling mechanical ventilation based upon both heuristic knowledge and physiological models. Heuristic knowledge is applied through hypothesis testing, e.g.…”

Journal of clinical monitoring and computing 2014 end of year summary: respiration

“…Schädler et al [32] evaluated a novel combined open and closed loop decision support system for automated weaning from mechanical ventilation. The system includes models of gas exchange and lung mechanics to simulate effect of changes in settings on physiological target values.…”