Prof. Lucia Lo Bello, PhD

Publication type:  Conference Proceeding

Authors: S. Baglio, A. Cammarata, P. Cortis, L. Lo Bello, P. D. Maddio, S. Nicosia, G. Patti, S. Sciberras, J. Scicluna, V. Scuderi, R. Sinatra, C. Trigona

Conference: IEEE International Symposium on Measurements & Networking (M&N 2019)

Address: Catania, Italy

Date: July 2019

Abstract:
The objective of this work concerns the study of virtual biosensors for the estimation of medical precursors. The principle is based on the combination of the signals coming from the patient (vital functions), the transduction of such acquired signals and the processing of the obtained information. The method will use n 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. 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 "track and trigger" and threshold (Early Warning Score) through the adoption of the Fuzzy Set Theory.

Keywords: Virtual biosensors; Fuzzy logic; Estimation of medical precursors

Publisher: IEEE

ISBN: 978-1-7281-1273-2

DOI:  10.1109/IWMN.2019.8805005

URL:  https://ieeexplore.ieee.org/abstract/document/8805005

Status: published

Cite as:
 S. Baglio, A. Cammarata, P. Cortis, L. Lo Bello, P. D. Maddio, S. Nicosia, G. Patti, S. Sciberras, J. Scicluna, V. Scuderi, R. Sinatra, C. Trigona, "Virtual biosensors for the estimation of medical precursors", IEEE International Symposium on Measurements & Networking (M&N 2019), Catania, Italy, July 2019

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