Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/117689
Title: Biosensors for monitoring of vital functional parameters during medical emergency
Authors: Zammit, David
Baylon, Vincenzo
Keywords: Biosensors
Fuzzy logic
Vital signs -- Measurement -- Data processing
Medicine -- Research -- Data processing
Emergency medicine
Signal processing
Issue Date: 2023
Publisher: Malta Chamber of Scientists
Citation: Zammit, D., & Baylon, V. (2023). Biosensors for monitoring of vital functional parameters during medical emergency. Xjenza, 11(1-2), 3-9.
Abstract: The objective of this work concerns the study of biosensors for monitoring of parameters and diagnosis of vital functional during first medical emergency. The study and analysis of vital parameters is extremely important in emergency medicine. The principle is based on the combination of the signals coming from the patient (vital functions), consists of measurement and comparison of the phase of active and reactive components of biologically active points (BAP) the transduction of such acquired signals and the processing of the obtained information. One of the advantages of reflex diagnostic methods is the fact that the response of BAPs to the change in the internal structure of the human body. These signals are proving instantaneous information on the functional state of 20 basic organ and system of the human body. The method will use one input variables (the classic physiological parameters and/or signals detected by using additive sensors) and one output variable which is correlated with the clinical condition of the patient. High information volume, accuracy, reliability, and reproducibility of data are supported in parallel in emergency diagnostics. A model will produce an association between the input variables and the output variable by using a data set established with the medical team. The proposed methodology improves standard systems such as reflex diagnostics, track and trigger and threshold (Early Warning Score). It is shown that good results for the prediction and early diagnosis in first medical emergency, through the adoption of the Fuzzy Set Theory.
URI: https://www.um.edu.mt/library/oar/handle/123456789/117689
ISSN: 18187269
Appears in Collections:Xjenza, 2023, Volume 11, Issue 1
Xjenza, 2023, Volume 11, Issue 1



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