Design and simulation of AI-based low-cost mechanical ventilator: An approach

被引:3
作者
Giri, Jayant [1 ]
Kshirsagar, Niraj [1 ]
Wanjari, Aishwary [1 ]
机构
[1] Yeshwantrao Chavan Coll Engn, Dept Mech Engn, Nagpur 442001, Maharashtra, India
关键词
Mechanical ventilator; COVID; 19; MATLAB; Simulink; PEEP; Machine learning; CNN;
D O I
10.1016/j.matpr.2021.04.369
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this situation of COVID 19, many people are being exposed to coronavirus, resulting in difficulty in breathing and a drop in oxygen percentage of blood. A mechanical ventilator is playing a vital role in tackling this situation but the ventilation process is neither readily available nor affordable. The idea behind this work is to propose a simplified design of a mechanical ventilator to reduce the cost and automate the Mechanical ventilation process. The simplified design, it's working, and required components are elaborated in this paper. The simulation of the proposed design is made in MATLAB/Simulink platform which is also discussed below. Taking into account the work done in the area of cost reduction of the mechanical ventilation process, the mechanical ventilator with a simplified design comprising of compressed air and oxygen source is being considered. The parameters considered for mechanical ventilation are positive end-expiratory pressure (PEEP), pressure wave, respiratory rate (RR), tidal volume, etc. These parameters of oxygen and air mixture are to be controlled with the help of electronic devices which are pressure regulator, solenoid valve, flow sensor, proportional valve, microprocessor, etc depending upon the condition of patient and type of disease. Simulation results are promising and precise which allows the study on ventilator model without jeopardizing the life of human subjects as in clinical approach and hides the complexity of computational models from the user. Furthermore, advancements in this model are done by the machine learning approach. (c) 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the Technology Innovation in Mechanical Engineering-2021.
引用
收藏
页码:5886 / 5891
页数:6
相关论文
共 50 条
  • [31] Design Space Exploration of a Multi-Model AI-Based Indoor Localization System
    Kotrotsios, Konstantinos
    Fanariotis, Anastasios
    Leligou, Helen-Catherine
    Orphanoudakis, Theofanis
    SENSORS, 2022, 22 (02)
  • [32] A Low-Cost Real Color Picker Based on Arduino
    Enrique Agudo, Juan
    Pardo, Pedro J.
    Sanchez, Hector
    Luis Perez, Angel
    Isabel Suero, Maria
    SENSORS, 2014, 14 (07): : 11943 - 11956
  • [33] A Predictive Maintenance Approach in Manufacturing Systems via AI-based Early Failure Detection
    Hosseinzadeh, Ali
    Chen, F. Frank
    Shahin, Mohammad
    Bouzary, Hamed
    MANUFACTURING LETTERS, 2023, 35 : 1179 - 1186
  • [34] Design of a Low-Cost Air Levitation System for Teaching Control Engineering
    Chacon, Jesus
    Saenz, Jacobo
    de la Torre, Luis
    Manuel Diaz, Jose
    Esquembre, Francisco
    SENSORS, 2017, 17 (10)
  • [35] Design and Development of Low-Cost, Portable, and Smart Chlorophyll-A Sensor
    Chowdhury, Rakibul Islam
    Wahid, Khan Arif
    Nugent, Katy
    Baulch, Helen
    IEEE SENSORS JOURNAL, 2020, 20 (13) : 7362 - 7371
  • [36] SoftFusion: A Low-Cost Approach to Enhance Reliability of Object Detection Applications
    Latifi, Salar
    Zamirai, Babak
    Mahlke, Scott
    2022 IEEE 40TH INTERNATIONAL CONFERENCE ON COMPUTER DESIGN (ICCD 2022), 2022, : 344 - 351
  • [37] A Machine Learning Approach to Low-Cost Photovoltaic Power Prediction Based on Publicly Available Weather Reports
    Maitanova, Nailya
    Telle, Jan-Simon
    Hanke, Benedikt
    Grottke, Matthias
    Schmidt, Thomas
    von Maydell, Karsten
    Agert, Carsten
    ENERGIES, 2020, 13 (03)
  • [38] A Conceptual Approach for an AI-Based Recommendation System for Handling Returns in Fashion E-Commerce
    Gry, Soeren
    Niederlaender, Marie
    Lodi, Aena Nuzhat
    Mutz, Marcel
    Werth, Dirk
    SMART BUSINESS TECHNOLOGIES, ICSBT 2023, 2024, 2132 : 1 - 23
  • [39] RanKer: An AI-Based Employee-Performance Classification Scheme to Rank and Identify Low Performers
    Patel, Keyur
    Sheth, Karan
    Mehta, Dev
    Tanwar, Sudeep
    Florea, Bogdan Cristian
    Taralunga, Dragos Daniel
    Altameem, Ahmed
    Altameem, Torki
    Sharma, Ravi
    MATHEMATICS, 2022, 10 (19)
  • [40] AI-Based Approach to Firewall Rule Refinement on High-Performance Computing Service Network
    Lee, Jae-Kook
    Hong, Taeyoung
    Lee, Gukhua
    APPLIED SCIENCES-BASEL, 2024, 14 (11):