A Multivent System for Non-invasive Ventilation: Solving the Problem of Ventilator Shortage during the COVID-19 Pandemic
IEEE Access
; : 1-1, 2023.
Article
Dans Anglais
| Scopus | ID: covidwho-20241894
ABSTRACT
The COVID-19 pandemic has caused a severe global problem of ventilator shortage. Placing multiple patients on a single ventilator (ventilator sharing) or dual patient ventilation has been proposed and conducted to increase the cure efficiency for ventilated patients. However, the ventilator-sharing method needs to use the same ventilator settings for all the patients, which cannot meet the ventilation needs of different patients. Therefore, a novel multivent system for non-invasive ventilation has been proposed in this study. The close loop system consists of the proportional valve and the flow-pressure sensor can regulate the airway pressure and flow for each patient. Multiple ventilation circuits can be combined in parallel to meet patients’ventilation demands simultaneously. Meanwhile, the mathematical model of the multivent system is established and validated through experiments. The experiments for different inspired positive airway pressure (IPAP), expired positive airway pressure (EPAP), inspiratory expiratory ratio (IE), and breath per minute (BPM) have been conducted and analyzed to test the performance of the multivent system. The results show that the multivent system can realize the biphasic positive airway pressure (BIPAP) ventilation mode in non-invasive ventilation without interfering among the three ventilation circuits, no matter the change of IPAP, EPAP, IE, and BPM. However, pressure fluctuation exists during the ventilation process because of the exhaust valve effect, especially in EPAP control. The control accuracy and stability need to be improved. Nevertheless, the novel designed multivent system can theoretically solve the problem of ventilator shortage during the COVID-19 pandemic and may bring innovation to the current mechanical ventilation system. Author
Texte intégral:
Disponible
Collection:
Bases de données des oragnisations internationales
Base de données:
Scopus
Type d'étude:
Étude pronostique
langue:
Anglais
Revue:
IEEE Access
Année:
2023
Type de document:
Article
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