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

• 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
• Institution: Ateneo De Manila University

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...