Waveform Tracker Alarm for Automatic Patient-Ventilator Asynchrony (PVA) and Mechanical State Recognition for Mechanical Ventilators Using Embedded Deep Learning

Waveform Tracker Alarm for Automatic Patient-Ventilator Asynchrony (PVA) and Mechanical State Recognition for Mechanical Ventilators Using Embedded Deep Learning

The Ateneo Innovation Center designs and develops a modular approach to medical alarm and alert systems for mechanical ventilators that enable clinicians to remotely monitor patient conditions and ventilator circuit status in near real-time, providing decision support that allows for a better diagno...

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Bibliographic Details
Main Authors: Santiago, Paul Ryan A., Cabacungan, Paul M., Oppus, Carlos M, Mamaradlo, John Paul A., Mercado, Neil Angelo M., Cao, Reymond P., Tangonan, Gregory L
Format: text
Published: Archīum Ateneo 2024
Subjects:
And circular electronics manufacturing
Biomedical monitoring
Emergency ventilator
Near cloud
TinyML
Biomedical
Computer Engineering
Electrical and Computer Engineering
Engineering
Online Access:https://archium.ateneo.edu/ecce-faculty-pubs/160
https://doi.org/10.1007/978-981-99-6523-6_10
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Institution: Ateneo De Manila University

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https://archium.ateneo.edu/ecce-faculty-pubs/160
https://doi.org/10.1007/978-981-99-6523-6_10

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