Tinyml Monitoring Techniques for A-Vent: An Iot Edge for Tracking Clinical Risk Outcomes and Automatic Detection of Patient-Ventilator Asynchrony
CoronaVirus disease 2019 (COVID-19) pandemic, is a respiratory tract infection disease, resulting in high demand for mechanical ventilators. Fronting healthcare workers facing work under pressure and great risk of getting infected due to high demand for care of COVID-19 patients. The COVID-19 pandem...
Saved in:
Main Author: | Santiago, Paul Ryan |
---|---|
Format: | text |
Published: |
Archīum Ateneo
2021
|
Subjects: | |
Online Access: | https://archium.ateneo.edu/theses-dissertations/475 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Ateneo De Manila University |
Similar Items
-
A Digital Twin Approach of A-vent Wireless Sensor for Real-Time and Predictive Monitoring of Patient Ventilator Asynchrony
by: Oppus, Carlos M, et al.
Published: (2023) -
Waveform Tracker Alarm for Automatic Patient-Ventilator Asynchrony (PVA) and Mechanical State Recognition for Mechanical Ventilators Using Embedded Deep Learning
by: Santiago, Paul Ryan A., et al.
Published: (2024) -
Patient-ventilator asynchronies: Types, outcomes and nursing detection skills
by: Enrico Bulleri, et al.
Published: (2019) -
Implementation of Home Automation System Using OPENHAB Framework for Heterogeneous IOT Devices
by: Parocha, Raymark
Published: (2019) -
Water Consumption Monitoring System with Fixture Recognition
by: Somontina, James Adrian
Published: (2020)