A novel healthcare 4.0 system for testing respiratory diseases based on nanostructured biosensors and fog networking

• A novel testing biosensing device with advanced nanostructured electrodes. • The collection of hydrogen peroxide in the exhaled breath without condensing it. • Personalized device for the remote self-testing of respiratory diseases. • Data-sharing infrastructure based on fog computing to enable screening programs. New digital healthcare models based on advanced bio-sensing technologies are regarded as a possible solution to improve the screening and prevention processes and the overall performance of healthcare supply chains. This is particularly relevant for respiratory diseases, which are currently among the first causes of death and medical expenditures in industrialized countries. This research proposes a new e-health model based on a fog architecture and a smart device, enabling remote diagnostics of respiratory diseases and allowing for decentralized patient testing and self-testing. According to such a model, the patients’ testing is executed through the analysis of the exhaled breath collected using a smart device based on a novel nanostructured sensor and transferring relevant information to the medical staff involved in the diagnosis process. This research proposes an original testing method and system, validated in the lab through a comparative analysis of culture media samples collected from healthy patients, and subsequently exposed to cigarette smoke extract (CSE, an inducer of oxidative stress). The preliminary results obtained demonstrate the validity of the approach proposed, encouraging further experimental analyses on human patients for the implementation into clinical practice.

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Publication Details

Journal
Computers & Industrial Engineering
Published
2024-11-04
DOI
https://doi.org/10.1016/j.cie.2024.110698
Citations
1
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.35
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article

A novel healthcare 4.0 system for testing respiratory diseases based on nanostructured biosensors and fog networking

Rosalinda Inguanta, Maria Ferraro, Serena Di Vincenzo, Giuseppe Aiello et al.
1 citations
Computers & Industrial Engineering
IoT and Edge/Fog Computing
0.35
article

A novel healthcare 4.0 system for testing respiratory diseases based on nanostructured biosensors and fog networking

Rosalinda Inguanta, Maria Ferraro, Serena Di Vincenzo, Giuseppe Aiello, Islam Asem Salah Abusohyon, Elisabetta Pace, Chiara Cipollina, Cinzia Muriana, Maria Giuseppina Bruno, Bernardo Patella, Mo’men Abu Sahyoun
article en
1 citations

Abstract

• A novel testing biosensing device with advanced nanostructured electrodes. • The collection of hydrogen peroxide in the exhaled breath without condensing it. • Personalized device for the remote self-testing of respiratory diseases. • Data-sharing infrastructure based on fog computing to enable screening programs. New digital healthcare models based on advanced bio-sensing technologies are regarded as a possible solution to improve the screening and prevention processes and the overall performance of healthcare supply chains. This is particularly relevant for respiratory diseases, which are currently among the first causes of death and medical expenditures in industrialized countries. This research proposes a new e-health model based on a fog architecture and a smart device, enabling remote diagnostics of respiratory diseases and allowing for decentralized patient testing and self-testing. According to such a model, the patients’ testing is executed through the analysis of the exhaled breath collected using a smart device based on a novel nanostructured sensor and transferring relevant information to the medical staff involved in the diagnosis process. This research proposes an original testing method and system, validated in the lab through a comparative analysis of culture media samples collected from healthy patients, and subsequently exposed to cigarette smoke extract (CSE, an inducer of oxidative stress). The preliminary results obtained demonstrate the validity of the approach proposed, encouraging further experimental analyses on human patients for the implementation into clinical practice.

Computers & Industrial EngineeringVol. 198
Istituto di Farmacologia Traslazionale (IT), Ri.MED (IT), National Research Council (IT), Yarmouk University (JO), University of Palermo (IT)
Openalex Percentile: Top 37%
IoT and Edge/Fog Computing
0.35
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