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An artificial intelligence-assisted portable low-cost device for the rapid detection of sars-cov-2

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An artificial intelligence-assisted portable low-cost device for the rapid detection of sars-cov-2. / Tharmakulasingam, M.; Chaudhry, N.S.; Fernando, A. et al.

In: Electronics (Switzerland), Vol. 10, No. 17, 2065, 26.08.2021.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Tharmakulasingam, M, Chaudhry, NS, Fernando, A, Branavan, M, Balachandran, W, Poirier, AC, Rohaim, MA, Munir, M & La Ragione, RM 2021, 'An artificial intelligence-assisted portable low-cost device for the rapid detection of sars-cov-2', Electronics (Switzerland), vol. 10, no. 17, 2065. https://doi.org/10.3390/electronics10172065

APA

Tharmakulasingam, M., Chaudhry, N. S., Fernando, A., Branavan, M., Balachandran, W., Poirier, A. C., Rohaim, M. A., Munir, M., & La Ragione, R. M. (2021). An artificial intelligence-assisted portable low-cost device for the rapid detection of sars-cov-2. Electronics (Switzerland), 10(17), [2065]. https://doi.org/10.3390/electronics10172065

Vancouver

Tharmakulasingam M, Chaudhry NS, Fernando A, Branavan M, Balachandran W, Poirier AC et al. An artificial intelligence-assisted portable low-cost device for the rapid detection of sars-cov-2. Electronics (Switzerland). 2021 Aug 26;10(17):2065. doi: 10.3390/electronics10172065

Author

Tharmakulasingam, M. ; Chaudhry, N.S. ; Fernando, A. et al. / An artificial intelligence-assisted portable low-cost device for the rapid detection of sars-cov-2. In: Electronics (Switzerland). 2021 ; Vol. 10, No. 17.

Bibtex

@article{0eb8bc9a5e074fc5acaa44c2369a8fa1,
title = "An artificial intelligence-assisted portable low-cost device for the rapid detection of sars-cov-2",
abstract = "An artificial intelligence-assisted low-cost portable device for the rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is presented here. This standalone temperature-controlled device houses tubes designed for conducting reverse transcription loop-mediated isothermal amplification (RT-LAMP) assays. Moreover, the device utilises tubes illuminated by LEDs, an in-built camera, and a small onboard computer with automated image acquisition and processing algorithms. This intelligent device significantly reduces the normal assay run time and removes the subjectivity associated with operator interpretation of colourimetric RT-LAMP results. To further improve this device{\textquoteright}s usability, a mobile app has been integrated into the system to control the LAMP assay environment and to visually display the assay results by connecting the device to a smartphone via Bluetooth. This study was undertaken using ~5000 images produced from the ~200 LAMP amplification assays using the prototype device. Synthetic RNA and a small panel of positive and negative SARS-CoV-2 patient samples were assayed for this study. State-of-the-art image processing and artificial intelligence algorithms were applied to these images to analyse them and to select the most efficient algorithm. The template matching algorithm for image extraction and MobileNet CNN architecture for classification results provided 98.0% accuracy with an average run time of 20 min to confirm the endpoint result. Two working points were chosen based on the best compromise between sensitivity and specificity. The high sensitivity point has a sensitivity value of 99.12% and specificity value of 70.8%, while at the high specificity point, the sensitivity is 96.05% and specificity 93.59%. Furthermore, this device provides an efficient and cost-effective platform for non-health professionals to detect not only SARS-CoV-2 but also other pathogens in resource-limited laboratories, factories, airports, schools, universities, and homes. ",
keywords = "Artificial intelligence, Image processing, LAMP, Portable device, Rapid detection, SARS-CoV-2",
author = "M. Tharmakulasingam and N.S. Chaudhry and A. Fernando and M. Branavan and W. Balachandran and A.C. Poirier and M.A. Rohaim and M. Munir and {La Ragione}, R.M.",
year = "2021",
month = aug,
day = "26",
doi = "10.3390/electronics10172065",
language = "English",
volume = "10",
journal = "Electronics (Switzerland)",
issn = "2079-9292",
publisher = "MDPI AG",
number = "17",

}

RIS

TY - JOUR

T1 - An artificial intelligence-assisted portable low-cost device for the rapid detection of sars-cov-2

AU - Tharmakulasingam, M.

AU - Chaudhry, N.S.

AU - Fernando, A.

AU - Branavan, M.

AU - Balachandran, W.

AU - Poirier, A.C.

AU - Rohaim, M.A.

AU - Munir, M.

AU - La Ragione, R.M.

PY - 2021/8/26

Y1 - 2021/8/26

N2 - An artificial intelligence-assisted low-cost portable device for the rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is presented here. This standalone temperature-controlled device houses tubes designed for conducting reverse transcription loop-mediated isothermal amplification (RT-LAMP) assays. Moreover, the device utilises tubes illuminated by LEDs, an in-built camera, and a small onboard computer with automated image acquisition and processing algorithms. This intelligent device significantly reduces the normal assay run time and removes the subjectivity associated with operator interpretation of colourimetric RT-LAMP results. To further improve this device’s usability, a mobile app has been integrated into the system to control the LAMP assay environment and to visually display the assay results by connecting the device to a smartphone via Bluetooth. This study was undertaken using ~5000 images produced from the ~200 LAMP amplification assays using the prototype device. Synthetic RNA and a small panel of positive and negative SARS-CoV-2 patient samples were assayed for this study. State-of-the-art image processing and artificial intelligence algorithms were applied to these images to analyse them and to select the most efficient algorithm. The template matching algorithm for image extraction and MobileNet CNN architecture for classification results provided 98.0% accuracy with an average run time of 20 min to confirm the endpoint result. Two working points were chosen based on the best compromise between sensitivity and specificity. The high sensitivity point has a sensitivity value of 99.12% and specificity value of 70.8%, while at the high specificity point, the sensitivity is 96.05% and specificity 93.59%. Furthermore, this device provides an efficient and cost-effective platform for non-health professionals to detect not only SARS-CoV-2 but also other pathogens in resource-limited laboratories, factories, airports, schools, universities, and homes.

AB - An artificial intelligence-assisted low-cost portable device for the rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is presented here. This standalone temperature-controlled device houses tubes designed for conducting reverse transcription loop-mediated isothermal amplification (RT-LAMP) assays. Moreover, the device utilises tubes illuminated by LEDs, an in-built camera, and a small onboard computer with automated image acquisition and processing algorithms. This intelligent device significantly reduces the normal assay run time and removes the subjectivity associated with operator interpretation of colourimetric RT-LAMP results. To further improve this device’s usability, a mobile app has been integrated into the system to control the LAMP assay environment and to visually display the assay results by connecting the device to a smartphone via Bluetooth. This study was undertaken using ~5000 images produced from the ~200 LAMP amplification assays using the prototype device. Synthetic RNA and a small panel of positive and negative SARS-CoV-2 patient samples were assayed for this study. State-of-the-art image processing and artificial intelligence algorithms were applied to these images to analyse them and to select the most efficient algorithm. The template matching algorithm for image extraction and MobileNet CNN architecture for classification results provided 98.0% accuracy with an average run time of 20 min to confirm the endpoint result. Two working points were chosen based on the best compromise between sensitivity and specificity. The high sensitivity point has a sensitivity value of 99.12% and specificity value of 70.8%, while at the high specificity point, the sensitivity is 96.05% and specificity 93.59%. Furthermore, this device provides an efficient and cost-effective platform for non-health professionals to detect not only SARS-CoV-2 but also other pathogens in resource-limited laboratories, factories, airports, schools, universities, and homes.

KW - Artificial intelligence

KW - Image processing

KW - LAMP

KW - Portable device

KW - Rapid detection

KW - SARS-CoV-2

U2 - 10.3390/electronics10172065

DO - 10.3390/electronics10172065

M3 - Journal article

VL - 10

JO - Electronics (Switzerland)

JF - Electronics (Switzerland)

SN - 2079-9292

IS - 17

M1 - 2065

ER -