MIT Emergency-Vent: An Automated Resuscitator Bag for the COVID-19 Crisis
Name
MIT_Emergency-Vent_An_Automated_Resuscitator_Bag_for_the_COVID-19_Crisis.pdf
Description
Published version
Size
3.9 MB
Format
Adobe PDF
Checksum (MD5)
950f13ddc1bd0b95cf2da8799dbb8a86
Author(s)
Ort, Teddy
Hanumara, Nevan
Antonini, Amado
Araki, Brandon
Abu-Khalaf, Murad
Detienne, Michael
Hagan, David
Jung, Kimberly
Ramirez, Aaron
Shaligram, Shakti
Date Issued
November 1, 2021
Journal
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Publisher
IEEE
Citation
T. Ort et al., "MIT Emergency-Vent: An Automated Resuscitator Bag for the COVID-19 Crisis," 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Mexico, 2021, pp. 4998-5004, doi: 10.1109/EMBC46164.2021.9630882.
Version
Final published version
Abstract
MIT's Emergency-Vent Project was launched in March 2020 to develop safe guidance and a reference design for a bridge ventilator that could be rapidly produced in a distributed manner worldwide. The system uses a novel servo-based robotic gripper to automate the squeezing of a manual resuscitator bag evenly from both sides to provide ventilation according to clinically specified parameters. In just one month, the team designed and built prototype ventilators, tested them in a series of porcine trials, and collaborated with industry partners to enable mass production. We released the design, including mechanical drawings, design spreadsheets, circuit diagrams, and control code into an open source format and assisted production efforts worldwide.Clinical relevance- This work demonstrated the viability of automating the compression of a manual resuscitator bag, with pressure feedback, to provide bridge ventilation support.
Description
43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Mexico, 2021
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/embc46164.2021.9630882
