Name
Abstract | ||
|---|---|---|
As current liver perfusion machines use pH probes for monitoring the acidity level in their machine, it poses an increased risk of contamination due to the probes direct contact with the blood, which would then greatly increase the risk of transplant failure. In order to detect pH levels of blood in a liver perfusion machine with minimal contact, this study will use computer vision as a tool in detecting and the given ph. In order to determine the pH level of blood, multiple computer vision techniques with built in knowledge-based systems will be used in the study. The knowledge-based system will continue to improve overtime as more data is collected. In this study, perfusion liquid will be used as the medium for blood due to ethical concerns. The pH is regulated using fuzzy logic control from the data taken from the pH detection system. Through the data taken from the results, it shows that this system when compared to the traditional pH monitoring system is accurate and viable in determining the pH level of the blood. And the system is viable in regulating the pH level of the system effectively. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ACIRS.2019.8936033 | 2019 4th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS) |
Keywords | Field | DocType |
pH regulation,computer vision,fuzzy logic | Computer vision,Transplant failure,Fuzzy logic control,Monitoring system,Computer science,Fuzzy logic,Liver perfusion,Artificial intelligence,Ph regulation,Ethical concerns,Perfusion | Conference |
ISBN | Citations | PageRank |
978-1-7281-2230-4 | 0 | 0.34 |
References | Authors | |
2 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tristan Joseph C. Limchesing | 1 | 0 | 0.34 |
| Rhen Anjerome R. Bedruz | 2 | 0 | 0.34 |
| Ryan Rhay P. Vicerra | 3 | 0 | 0.34 |
| John Anthony Jose | 4 | 0 | 0.34 |
| Nilo Bugtai | 5 | 0 | 0.34 |