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Design, Simulation, and Development of a BioSensor for Viruses Detection Using FPGA

Objective: Impedance based biosensing provides a unique, highly sensitive electrical approach to biomolecule detection, cell growth, and other biological events. To date, an impedance change due to the cell growth has been considered as a solution to detect some changes in a cell’s behavior. The imp...

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Detalles Bibliográficos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IEEE 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7880301/
https://www.ncbi.nlm.nih.gov/pubmed/33598367
http://dx.doi.org/10.1109/JTEHM.2021.3055984
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collection PubMed
description Objective: Impedance based biosensing provides a unique, highly sensitive electrical approach to biomolecule detection, cell growth, and other biological events. To date, an impedance change due to the cell growth has been considered as a solution to detect some changes in a cell’s behavior. The impedance change detection is normally measured via an impedance analyzer which is expensive and also cumbersome. Rapid and definitive diagnosis of viral infections is imperative in patient treatment process. Early detection followed by appropriate lifestyle and treatment may result to a longer, healthier life. Certain patients require continues monitoring that may require regular visits to hospitals which is not practical. Therefore, a continuous home healthcare device is needed to monitor and detect any change in a patient’s health condition. Methods & Results: In this research, a novel sensor and healthcare monitoring system is modeled, simulated, developed, and tested to detect viruses by detecting the change in the impedance due to antibodies and antigens binding. First, COMSOL simulation tool is used to develop a model to prove the concept. The model predicts increasing impedance during functionalization of electrodes with antibodies and after antigen binding steps. Second, to understand how nanoscale electrode size and spacing would affect biosensing assay (antibody-based affinity binding of a protein antigen), a model using COMSOL is developed. Third, Field Programmable Gate Arrays (FPGA) based signal processing system is developed as well to be connected to analog to digital converter (ADC) to acquire the current and voltage readings of the sensors over time. This healthcare monitoring system is used to continuously monitoring a patient’s condition and reports any changes in the impedance readings which represents virus detection or at least change in the cell’s behavior. Conclusions: The proposed sensor model is simulated, tested and verified via COMSOL and the FPGA prototype is tested and it verified the COMSOL model. This work reports that the proposed sensor can be used to detect viruses via detecting a change in the impedance.
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spelling pubmed-78803012021-02-16 Design, Simulation, and Development of a BioSensor for Viruses Detection Using FPGA IEEE J Transl Eng Health Med Article Objective: Impedance based biosensing provides a unique, highly sensitive electrical approach to biomolecule detection, cell growth, and other biological events. To date, an impedance change due to the cell growth has been considered as a solution to detect some changes in a cell’s behavior. The impedance change detection is normally measured via an impedance analyzer which is expensive and also cumbersome. Rapid and definitive diagnosis of viral infections is imperative in patient treatment process. Early detection followed by appropriate lifestyle and treatment may result to a longer, healthier life. Certain patients require continues monitoring that may require regular visits to hospitals which is not practical. Therefore, a continuous home healthcare device is needed to monitor and detect any change in a patient’s health condition. Methods & Results: In this research, a novel sensor and healthcare monitoring system is modeled, simulated, developed, and tested to detect viruses by detecting the change in the impedance due to antibodies and antigens binding. First, COMSOL simulation tool is used to develop a model to prove the concept. The model predicts increasing impedance during functionalization of electrodes with antibodies and after antigen binding steps. Second, to understand how nanoscale electrode size and spacing would affect biosensing assay (antibody-based affinity binding of a protein antigen), a model using COMSOL is developed. Third, Field Programmable Gate Arrays (FPGA) based signal processing system is developed as well to be connected to analog to digital converter (ADC) to acquire the current and voltage readings of the sensors over time. This healthcare monitoring system is used to continuously monitoring a patient’s condition and reports any changes in the impedance readings which represents virus detection or at least change in the cell’s behavior. Conclusions: The proposed sensor model is simulated, tested and verified via COMSOL and the FPGA prototype is tested and it verified the COMSOL model. This work reports that the proposed sensor can be used to detect viruses via detecting a change in the impedance. IEEE 2021-02-01 /pmc/articles/PMC7880301/ /pubmed/33598367 http://dx.doi.org/10.1109/JTEHM.2021.3055984 Text en https://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Design, Simulation, and Development of a BioSensor for Viruses Detection Using FPGA
title Design, Simulation, and Development of a BioSensor for Viruses Detection Using FPGA
title_full Design, Simulation, and Development of a BioSensor for Viruses Detection Using FPGA
title_fullStr Design, Simulation, and Development of a BioSensor for Viruses Detection Using FPGA
title_full_unstemmed Design, Simulation, and Development of a BioSensor for Viruses Detection Using FPGA
title_short Design, Simulation, and Development of a BioSensor for Viruses Detection Using FPGA
title_sort design, simulation, and development of a biosensor for viruses detection using fpga
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7880301/
https://www.ncbi.nlm.nih.gov/pubmed/33598367
http://dx.doi.org/10.1109/JTEHM.2021.3055984
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