A Digital Twin Approach of A-vent Wireless Sensor for Real-Time and Predictive Monitoring of Patient Ventilator Asynchrony
Prior to the recent work on a low-cost Ateneo mechanical ventilator machine named A-vent, this study demonstrated a simple Digital Twin approach for a real-time monitoring system that can be useful to any mechanical ventilator unit. Previous research concentrated on A-vent design, Near Cloud data ca...
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Archīum Ateneo
2023
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Online Access: | https://archium.ateneo.edu/ecce-faculty-pubs/153 https://doi.org/10.1109/ECAI58194.2023.10194042 |
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ph-ateneo-arc.ecce-faculty-pubs-11472024-02-21T06:36:25Z A Digital Twin Approach of A-vent Wireless Sensor for Real-Time and Predictive Monitoring of Patient Ventilator Asynchrony Oppus, Carlos M Santiago, Paul Ryan A. Torres, Justin Bryce M. Mercado, Neil Angelo M. Cabacungan, Paul M. Cao, Reymond P. Cabacungan, Nerissa G. Tangonan, Gregory L Prior to the recent work on a low-cost Ateneo mechanical ventilator machine named A-vent, this study demonstrated a simple Digital Twin approach for a real-time monitoring system that can be useful to any mechanical ventilator unit. Previous research concentrated on A-vent design, Near Cloud data caching, and Machine Learning model development. However, it lacks Internet of Things capabilities for remote monitoring applications. This work incorporates new software components to a Near Cloud server that stores and monitors the ventilator and patient data across the wireless network. Wireless sensor nodes attached to the A-vent and patient interaction model capture the time-series waveform of the ventilator, its predictive analysis, and oximeter values. The data queries command displays the data stored in the Near Cloud databases on the monitoring dashboard. It shows a digital representation of the system, allowing real-time updates to be viewed remotely and easily comprehended. 2023-01-01T08:00:00Z text https://archium.ateneo.edu/ecce-faculty-pubs/153 https://doi.org/10.1109/ECAI58194.2023.10194042 Electronics, Computer, and Communications Engineering Faculty Publications Archīum Ateneo Biomedical Sensor Digital Twin Healthcare Internet of Medical Things TinyML Biomedical Electrical and Computer Engineering Engineering |
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Biomedical Sensor Digital Twin Healthcare Internet of Medical Things TinyML Biomedical Electrical and Computer Engineering Engineering Oppus, Carlos M Santiago, Paul Ryan A. Torres, Justin Bryce M. Mercado, Neil Angelo M. Cabacungan, Paul M. Cao, Reymond P. Cabacungan, Nerissa G. Tangonan, Gregory L A Digital Twin Approach of A-vent Wireless Sensor for Real-Time and Predictive Monitoring of Patient Ventilator Asynchrony |
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Prior to the recent work on a low-cost Ateneo mechanical ventilator machine named A-vent, this study demonstrated a simple Digital Twin approach for a real-time monitoring system that can be useful to any mechanical ventilator unit. Previous research concentrated on A-vent design, Near Cloud data caching, and Machine Learning model development. However, it lacks Internet of Things capabilities for remote monitoring applications. This work incorporates new software components to a Near Cloud server that stores and monitors the ventilator and patient data across the wireless network. Wireless sensor nodes attached to the A-vent and patient interaction model capture the time-series waveform of the ventilator, its predictive analysis, and oximeter values. The data queries command displays the data stored in the Near Cloud databases on the monitoring dashboard. It shows a digital representation of the system, allowing real-time updates to be viewed remotely and easily comprehended. |
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text |
author |
Oppus, Carlos M Santiago, Paul Ryan A. Torres, Justin Bryce M. Mercado, Neil Angelo M. Cabacungan, Paul M. Cao, Reymond P. Cabacungan, Nerissa G. Tangonan, Gregory L |
author_facet |
Oppus, Carlos M Santiago, Paul Ryan A. Torres, Justin Bryce M. Mercado, Neil Angelo M. Cabacungan, Paul M. Cao, Reymond P. Cabacungan, Nerissa G. Tangonan, Gregory L |
author_sort |
Oppus, Carlos M |
title |
A Digital Twin Approach of A-vent Wireless Sensor for Real-Time and Predictive Monitoring of Patient Ventilator Asynchrony |
title_short |
A Digital Twin Approach of A-vent Wireless Sensor for Real-Time and Predictive Monitoring of Patient Ventilator Asynchrony |
title_full |
A Digital Twin Approach of A-vent Wireless Sensor for Real-Time and Predictive Monitoring of Patient Ventilator Asynchrony |
title_fullStr |
A Digital Twin Approach of A-vent Wireless Sensor for Real-Time and Predictive Monitoring of Patient Ventilator Asynchrony |
title_full_unstemmed |
A Digital Twin Approach of A-vent Wireless Sensor for Real-Time and Predictive Monitoring of Patient Ventilator Asynchrony |
title_sort |
digital twin approach of a-vent wireless sensor for real-time and predictive monitoring of patient ventilator asynchrony |
publisher |
Archīum Ateneo |
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2023 |
url |
https://archium.ateneo.edu/ecce-faculty-pubs/153 https://doi.org/10.1109/ECAI58194.2023.10194042 |
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