Design and validation of an automated testing system for essential performance parameters of ventilators_Journal of Biomedical Engineering

Authors：

LI Yongzhen ^1,2 , WANG Wei ³ , ZHANG Chunyuan ³ , ZHANG Xia ² ,  CHEN Zhenglong ¹ , HU Zhaoyan ¹

1. School of Medical Instruments, Shanghai University of Medicine & Health Sciences, Shanghai 201318, P. R. China;
2. School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China;
3. Shanghai Institute of Medical Device Testing, Shanghai 201318, P. R. China;

Corresponding author：

CHEN Zhenglong, Email: czlclx@sina.com

Keywords：

Ventilator; Automated testing; Tidal volume; Oxygen concentration; Positive end expiratory pressure

DOI：

10.7507/1001-5515.202408009

Video：

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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.

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1. Zhang P, Sun J, Wan G, et al. Development of ventilator tester calibration equipment//2015 IET International Conference on Biomedical Image and Signal Processing (ICBISP 2015). Beijing: Institution of Engineering and Technology, 2015: 1-4.
2. Govoni L, Dellacà R L, Peñuelas O, et al. Actual performance of mechanical ventilators in ICU: a multicentric quality control study. Medical Devices: Evidence and Research, 2012, 5: 111-119.
3. Rafols-de-Urquia M, Estrada L, Estevez-Piorno J, et al. Evaluation of a wearable device to determine cardiorespiratory parameters from surface diaphragm electromyography. IEEE Journal of Biomedical and Health Informatics, 2019, 23(5): 1964-1971.
4. Duan X, Song X, Yang C, et al. Evaluation of three approaches used for respiratory measurement in healthy subjects. Physiological Measurement, 2023, 44(10): 105004.
5. 王永言, 马嵩华, 胡天亮, 等. 基于专家知识的呼吸机参数设置与无级自适应调节策略. 生物医学工程学杂志, 2023, 40(5): 945-952.
6. 李德旺, 仇原鹰, 盛英. 呼吸力学参数测量方法的研究. 生物医学工程学杂志, 2006, 23(4): 770-773.
7. Beydon L, Liu N, Hassapopoulos J, et al. Test of 20 similar intensive care ventilators in daily use conditions evaluation of accuracy and performances. Intensive Care Med, 1992, 18(1): 32-37.
8. 叶锦田. 呼吸机的维护与保养. 医疗装备, 2019, 32(5): 119-120.
9. 黄海明. 呼吸机校准中若干问题的探讨. 品牌与标准化, 2024, 384(1): 186-188.
10. 王桑. 呼吸机校准中的常见问题分析及保养措施. 品牌与标准化, 2023, 383(6): 46-48.
11. 王伟, 马小建. 呼吸机通气性能自动化测试系统研究和设计. 中国医疗器械杂志, 2023, 47(5): 518-522.
12. Samodro R A, Ginanjar G, Prihhapso Y, et al. Design and realization of a mobile-automatic calibration system for ventilator testers: oxygen concentration. Journal of Physics: Conference Series, 2023, 2498(1): 012023.
13. Farré R, Navajas D, Prats E, et al. Performance of mechanical ventilators at the patient’s home: a multicentre quality control study. Thorax, 2006, 61(5): 400-404.
14. 国家药品监督管理局. GB 9706.212-2020医用电气设备第2-12部分: 重症护理呼吸机的基本安全和基本性能专用要求. 北京: 中国标准出版社, 2020.
15. 北京谊安医疗系统股份有限公司. 呼吸支持设备自动化试通气的方法和系统: 中国, CN201811625369.6. 2019-05-07.
16. 朱新萍. PF300系列测量仪在现代化科技中的应用. 上海计量测试, 2000, 170(2): 49.
17. 许昱晟. 不同顺应性和阻力的模拟肺对呼吸机潮气量输出准确性的影响. 中国医疗器械信息, 2023, 29(9): 42-44,52.
18. Li X, Tan W, Zhao H, et al. Effects of jet nebulization on ventilator performance with different invasive ventilation modes: a bench study. Frontiers in Medicine(Lausanne). 2022, 9: 1004551.
19. Moore M N, Picone D S, Callisaya M L, et al. Comparison of manual and automated auscultatory blood pressure during graded exercise among people with type 2 diabetes. The Journal of Clinical Hypertension, 2019, 21(12): 1872-1878.
20. Hao L, Li X, Shi Y, et al. Mechanical ventilation strategy for pulmonary rehabilitation based on patient-ventilator interaction. Science China Technological Sciences, 2021, 64(4): 869-878.
21. Ottaviani V, Veneroni C, Dell’Orto V, et al. Accuracy of volume and pressure delivery by mechanical ventilators in use in neonatal intensive care units: a quality control study. Pediatric Pulmonology, 2020, 55(8): 1955-1962.
22. Nève V, Leclerc F, Noizet O, et al. Influence of respiratory system impedance on volume and pressure delivered at the Y piece in ventilated infants. Pediatric Critical Care Medicine, 2003, 4(4): 418-425.
23. Vignaux L, Piquilloud L, Tourneux P, et al. Neonatal and adult ICU ventilators to provide ventilation in neonates, infants, and children: a bench model study. Respiratory Care, 2014, 59(10): 1463-1475.
24. Liu J, Zheng W, Wang Z. Test and development of a specialized pipeline for ventilator calibration. Critical Reviews in Biomedical Engineering, 2023, 51(6): 17-28.

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