Title: An affordable, intelligent, and fully functional smart ventilator system

Authors: Bharath Krishnan; Achuth Karakkat; Rohith Mohan Menon; Shriram K. Vasudevan

Addresses: Department of Computer Science and Engineering, Amrita School of Engineering, Ettimadai, Coimbatore Amrita Vishwa Vidyapeetham, 641112, India ' Department of Computer Science and Engineering, Amrita School of Engineering, Ettimadai, Coimbatore Amrita Vishwa Vidyapeetham, 641112, India ' Department of Computer Science and Engineering, Amrita School of Engineering, Ettimadai, Coimbatore Amrita Vishwa Vidyapeetham, 641112, India ' K. Ramakrishnan College of Technology, Kariyamanikam Road, Samayapuram – 621112, Trichy, Tamilnadu, India

Abstract: Because of the coronavirus disease (COVID-19) pandemic scenario that the world is going through right now, there has been a surge in the requirement for emergency life support systems like ventilators. Conventional ventilators used in intensive care units (ICUs) tend to be bulky and expensive and demand high power consumption and trained experts to operate. The aim of the project is to deliver a solution for the growing demand for portable ventilators and a viable replacement for nurse assisted artificial resuscitation. Mechanical ventilation is the process of supplying scheduled breaths to a patient who lacks the ability to do the work of breathing (WOB) himself/herself. The pattern of breathing for every patient is identified using sensor(s) and the required volume of air is supplied by compressing a bag valve mask (BVM) device. A machine learning algorithm learns the pattern of breathing and adjusts the pressure and volume controls specific to every patient. All operations and control mode switching for the device can be done using an Android app, hence making it user friendly.

Keywords: COVID-19; coronavirus; intensive care unit; ICU; ventilator; smart ventilator; breathing issues.

DOI: 10.1504/IJMEI.2022.126525

International Journal of Medical Engineering and Informatics, 2022 Vol.14 No.6, pp.550 - 563

Received: 09 Dec 2020
Accepted: 09 Jan 2021
Published online: 28 Oct 2022 *

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