RESUMEN
OBJECTIVE@#In order to grasp the quality status of the first-aid ventilator in pre-hospital and field environment in time, the quality control and detection items of invasive ventilator were optimized to form a rapid detection operation process of first-aid ventilator and ensure the safety of patient treatment.@*METHODS@#Based on the quality control detection data of invasive ventilator in hospital in recent years, methods such as narrowing the range of qualified criteria and analyzing confidence interval were adopted to extract indicators prone to deviation and verify their correlation with similar indicators, so as to form an optimized rapid detection portfolio.@*RESULTS@#Compared with the original quality control detection procedures, the detection indicators of the rapid detection procedures were reduced from 5 categories of 24 indicators to 3 categories of 7 indicators. The detection time was shortened by 56.1% and the coincidence rate of the detection results was 100% after the actual measurement and verification.@*CONCLUSIONS@#Under the premise of ensuring the testing quality, the operating procedure for rapid detection of emergency ventilator can greatly reduce the detection time, and realize the rapid and high frequency quality control detection, so as to ensure the quality and safety of the equipment.
Asunto(s)
Humanos , Servicios de Atención de Salud a Domicilio , Control de Calidad , Ventiladores MecánicosRESUMEN
This paper is to build a finite element model of brain with a real brain shapeon which simulation studies of electrical impedance tomography EIT in the brain is based. A curve of a real brain shape is simulated with the curve-fitting methods and EIT in the brain is finished with finite-element methods and Equipotential Lines Back-Projection algorithm.The locationarea and amplitude of the change of the resistivity are reconstructed accurately. But the image quality has to be further improved.This paper provides a basis for clinical applications of EIT in brain.