IoT and Biosensors: A Smart Portable Potentiostat With Advanced Cloud-Enabled Features

Bianchi, Valentina; Boni, Andrea; Bassoli, Marco; Giannetto, Marco; Fortunati, Simone; Careri, Maria; Munari, Ilaria De

doi:10.1109/access.2021.3120022

Cited by 18 publications

(13 citation statements)

References 31 publications

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“…The resulting peak intensity acquired by means of DPV was proportional to the amount of GAR-AP and, in turn, of the SARS-CoV-2 S1 subunit bound to the receptor. DPV analysis was performed using the smart portable potentiostat previously developed and described in [ 41 ], where a performance equivalent to that of a commercial benchtop potentiostat was proven.…”

Section: Resultsmentioning

confidence: 99%

“…The smart potentiostat described in [ 41 ] has proven to be suitable for data acquisition. It is a portable wireless device that uses the Wi-Fi protocol to connect to a cloud environment for data processing and visualization.…”

Section: Methodsmentioning

confidence: 99%

“…The device, which is shown in Figure 2 , consists of a custom Analog Front End (AFE) interfaced with a microcontroller that embeds a Wi-Fi network processor (i.e., CC3200 by Texas Instruments) [ 41 ]. Its dimensions are 12 × 8 × 6 cm (LxWxH) for a weight of 200 g. The device can be powered by two 1.5V AA batteries.…”

Section: Methodsmentioning

confidence: 99%

“…The immunosensor was interfaced with a WiFi-based portable device for signal readout and on-cloud data processing which enables ML features [ 41 ]. This IoT portable potentiostat was connected through a Wi-Fi protocol with the Thingspeak cloud service, which consists of an IoT data analytics platform with the ability to use MATLAB for data analyses [ 42 ].…”

Section: Introductionmentioning

confidence: 99%

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Rapid Quantification of SARS-Cov-2 Spike Protein Enhanced with a Machine Learning Technique Integrated in a Smart and Portable Immunosensor

et al. 2022

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An IoT-WiFi smart and portable electrochemical immunosensor for the quantification of SARS-CoV-2 spike protein was developed with integrated machine learning features. The immunoenzymatic sensor is based on the immobilization of monoclonal antibodies directed at the SARS-CoV-2 S1 subunit on Screen-Printed Electrodes functionalized with gold nanoparticles. The analytical protocol involves a single-step sample incubation. Immunosensor performance was validated in a viral transfer medium which is commonly used for the desorption of nasopharyngeal swabs. Remarkable specificity of the response was demonstrated by testing H1N1 Hemagglutinin from swine-origin influenza A virus and Spike Protein S1 from Middle East respiratory syndrome coronavirus. Machine learning was successfully used for data processing and analysis. Different support vector machine classifiers were evaluated, proving that algorithms affect the classifier accuracy. The test accuracy of the best classification model in terms of true positive/true negative sample classification was 97.3%. In addition, the ML algorithm can be easily integrated into cloud-based portable Wi-Fi devices. Finally, the immunosensor was successfully tested using a third generation replicating incompetent lentiviral vector pseudotyped with SARS-CoV-2 spike glycoprotein, thus proving the applicability of the immunosensor to whole virus detection.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Rapid Quantification of SARS-Cov-2 Spike Protein Enhanced with a Machine Learning Technique Integrated in a Smart and Portable Immunosensor

et al. 2022

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“…Multiplex electrochemical point-of-care testing (ME-POCT) devices are expected to have four major compartments: 1) reliable and reproducible electrodes created using inkjet or screen printing methods, 2) an accurate biosensing protocol for mediating the electrode surface to create accurate biosensors, 3) microfluidics for automating electrochemical biosensing steps, and 4) and an accurate and low-cost multichannel potentiostat with an easy-to-use interface for data interpretation and wireless data transfer. Despite enormous advances in developing multiplex screen printed electrodes and electrochemical biosensors ( Dhanapala et al, 2020 ; Khetani et al, 2019 ; Kinnamon et al, 2018 ; Noah and Ndangili, 2019 ; Salahandish et al 2019 , 2022a ) as well as the recent progress in self-powered microfluidic devices ( Haghayegh et al 2022a , 2022b ; Nyein et al, 2018 ; Salahandish et al, 2022b ), the realization of ME-POCT requires the development of new hand-held, rapid and remote reading, easy-to-use, noise-free, and cheaper multichannel potentiostat readers ( Alam et al, 2020 ; Bianchi et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

A compact, low-cost, and binary sensing (BiSense) platform for noise-free and self-validated impedimetric detection of COVID-19 infected patients

Salahandish

Jalali

Tabrizi

et al. 2022

Biosensors and Bioelectronics

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Metrological traceability in process analytical technologies and point-of-need technologies for food safety and quality control: not a straightforward issue

et al. 2022

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Traditional techniques for food analysis are based on off-line laboratory methods that are expensive and time-consuming and often require qualified personnel. Despite the high standards of accuracy and metrological traceability, these well-established methods do not facilitate real-time process monitoring and timely on-site decision-making as required for food safety and quality control. The future of food testing includes rapid, cost-effective, portable, and simple methods for both qualitative screening and quantification of food contaminants, as well as continuous, real-time measurement in production lines. Process automatization through process analytical technologies (PAT) is an increasing trend in the food industry as a way to achieve improved product quality, safety, and consistency, reduced production cycle times, minimal product waste or reworks, and the possibility for real-time product release. Novel methods of analysis for point-of-need (PON) screening could greatly improve food testing by allowing non-experts, such as consumers, to test in situ food products using portable instruments, smartphones, or even visual naked-eye inspections, or farmers and small producers to monitor products in the field. This requires the attention of the research community and devices manufacturers to ensure reliability of measurement results from PAT strategy and PON tests through the demonstration and critical evaluation of performance characteristics. The fitness for purpose of methods in real-life conditions is a priority that should not be overlooked in order to maintain an effective and harmonized food safety policy. Graphical Abstract

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IoT and Biosensors: A Smart Portable Potentiostat With Advanced Cloud-Enabled Features

Abstract: This work was supported by the project "Biosensoristica innovativa per i test sierologici e molecolari e nuovi dispositivi PoCT per la diagnosi di infezione da SARS-CoV-2" funded in 2020 by "Bando Straordinario di Ateneo per Progetti di Ricerca Biomedica in Ambito SARS-COV-2 e COVID-19" -

Cited by 18 publications

References 31 publications

Rapid Quantification of SARS-Cov-2 Spike Protein Enhanced with a Machine Learning Technique Integrated in a Smart and Portable Immunosensor

Rapid Quantification of SARS-Cov-2 Spike Protein Enhanced with a Machine Learning Technique Integrated in a Smart and Portable Immunosensor

A compact, low-cost, and binary sensing (BiSense) platform for noise-free and self-validated impedimetric detection of COVID-19 infected patients

Metrological traceability in process analytical technologies and point-of-need technologies for food safety and quality control: not a straightforward issue

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