摘要
以传统人工方式检测呼吸机通气性能,工作量巨大、检测周期长、数据记录繁琐易错,难以满足当下呼吸机研发制造对检测效率的要求,因此本研究设计了一套呼吸机关键性能参数自动化测试系统。该系统主要包括呼吸机气流分析仪、模拟肺自动切换模块和测试控制平台三部分。在测试软件的控制下,该系统能够实现呼吸机关键性能参数的自动化测试,并生成最终的测试结果报告。为验证本文设计系统的有效性,使用该自动化测试系统和传统人工检测方法,分别对两种不同品牌的呼吸机在四种不同工况下的潮气量、氧浓度和呼气末正压精度进行测试。布兰德—阿尔特曼(Bland-Altman)统计方法分析表明,上述所有呼吸参数的自动化测试精度与人工测试精度二者具有良好的一致性;在检测效率方面,自动化测试系统检测用时约为人工检测的1/3。研究结果表明,本文设计的自动化测试系统为呼吸机的质量检测和计量校准提供了一种全新的方法与手段,具有广泛的应用前景。
Traditional manual testing of ventilator performance is labor-intensive,time-consuming,and prone to errors in data recording,making it difficult to meet the current demands for testing efficiency in the development and manufacturing of ventilators.Therefore,in this study we designed an automated testing system for essential performance parameters of ventilators.The system mainly comprises a ventilator airflow analyzer,an automated switch module for simulated lungs,and a test control platform.Under the control of testing software,this system can perform automated tests of critical performance parameters of ventilators and generate a final test report.To validate the effectiveness of the designed system,tests were conducted on two different brands of ventilators under four different operating conditions,comparing tidal volume,oxygen concentration,and positive end expiratory pressure accuracy using both the automated testing system and traditional manual methods.Bland-Altman statistical analysis indicated good consistency between the accuracy of automated tests and manual tests for all respiratory parameters.In terms of testing efficiency,the automated testing system required approximately one-third of the time needed for manual testing.These results demonstrate that the designed automated testing system provides a novel approach and means for quality inspection and measurement calibration of ventilators,showing broad application prospects.
作者
李咏臻
王伟
张春元
张夏
陈正龙
胡兆燕
LI Yongzhen;WANG Wei;ZHANG Chunyuan;ZHANG Xia;CHEN Zhenglong;HU Zhaoyan(School of Medical Instruments,Shanghai University of Medicine&Health Sciences,Shanghai 201318,P.R.China;School of Health Science and Engineering,University of Shanghai for Science and Technology,Shanghai 200093,P.R.China;Shanghai Institute of Medical Device Testing,Shanghai 201318,P.R.China)
出处
《生物医学工程学杂志》
2025年第1期164-173,共10页
Journal of Biomedical Engineering
基金
国家自然科学基金面上项目(12372384)
上海市自然科学基金(21ZR1428300)。
关键词
呼吸机
自动化测试
潮气量
氧浓度
呼气末正压
Ventilator
Automated testing
Tidal volume
Oxygen concentration
Positive end expiratory pressure
