Towards the Development of Rapid and Low-Cost Pathogen Detection Systems Using Microfluidic Technology and Optical Image Processing
Source abstract
Abstract
Waterborne pathogens affect all waters globally and proceed to be an ongoing concern. Previous methods for detection of pathogens consist of a high test time and a high sample consumption, but they are very expensive and require specialist operators. This study aims to develop a monitoring system capable of identifying waterborne pathogens with particular characteristics using a microfluidic device, optical imaging and a classification algorithm to provide low-cost and portable solutions. This paper investigates the detection of small size microbeads (1–5 µm) from a measured water sample by using a cost-effective microscopic camera and computational algorithms. Results provide areas of opportunities to decrease sample consumption, reduce testing time and minimize the use of expensive equipment.
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Research context
OpenAlex topics: Biosensors and Analytical Detection · Microfluidic and Bio-sensing Technologies · Microfluidic and Capillary Electrophoresis Applications
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Affiliations
School of Engineering and the Built Environment, Edinburgh Napier University, Edinburgh EH10 5DT, UK
School of Computing, Edinburgh Napier University, Edinburgh EH10 5DT, UK
References (23)
Show source-provided references
1. World Health Organization (WHO) (2020, February 29). “Drinking Water”. Available online: https://www.who.int/topics/drinking_water/en/.
2. World Health Organization (WHO) (2020, February 29). “Top 10 Causes of Death”. Available online: https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death.
3. (2020, February 29). Cryptosporidium: Drinking Water Health Advisory. EPA-822-R-01-009, Available online: https://www.epa.gov/sites/production/files/2015-10/documents/cryptosporidium-report.pdf.
4. Megasonic sonication for cost-effective and automatable elution of cryptosporidium from filters and membranes10.1016/j.mimet.2015.09.001 ↗
5. Method 1623.1, 2012 (2012). Method 1623.1: Cryptosporidium and Giardia in Water by Filtration/IMS/FA, Environmental Protection Agency.
6. Bridle, H. (2014). Overview of Waterborne Pathogens, Waterborne Pathogens: Detection Methods and Applications, Academic Press. [1st ed.].10.1016/B978-0-444-59543-0.00002-5 ↗
7. The origins and the future of microfluidics10.1038/nature05058 ↗
8. Tian, W.C., and Finehout, E. (2008). Microfluidic Diagnostic Systems for the Rapid Detection and Quantification of Pathogens, Microfluidics for Biological Applications, Springer.10.1007/978-0-387-09480-9_9 ↗
9. Meyers, R. (2009). Microfluidics. Encyclopaedia of Complexity and Systems Science, Springer.10.1007/978-0-387-30440-3 ↗
10. Monitoring of drinking water quality using automated ATP quantification10.1016/j.mimet.2019.105713 ↗
11. A centrifugal microfluidics platform for potential application on immobilization-free bead-based immunoassays10.4028/www.scientific.net/AMM.289.39 ↗
12. Application of microfluidics in waterborne pathogen monitoring: A review10.1016/j.watres.2014.01.061 ↗
13. Maxine, Y. (2019). A review of state-of-the-art microfluidic technologies for environmental applications: Detection and remediation. Glob. Chall., 3.10.1002/gch2.201800060 ↗
14. New advances in microfluidic flow cytometry10.1002/elps.201800298 ↗
15. Lukes, J.R., and Hong, J. (2015). Flow Cytometer Lab-on-a-Chip Devices, Encyclopaedia of Microfluidics and Nanofluidics, Springer.10.1007/978-1-4614-5491-5_546 ↗
16. Wu, M., Piccini, M., Koh, C.Y., Lam, K.S., and Singh, A.K. (2013). Single cell microRNA analysis using microfluidic flow cytometry. PLoS ONE, 8.10.1371/journal.pone.0055044 ↗
17. The intersection of flow cytometry with microfluidics and microfabrication10.1039/C3LC51152A ↗
18. Ditterich, P.S., Malik, F., and Schwille, P. (2007). Cytometry on Microfluidic Chips, Microfluidic Technologies for Miniaturized Analysis Systems, Springer. Chapter 14.
19. Lin, C.L., Chang, W.H., Wang, C.H., Lee, C.H., Chen, T.Y., Jan, F.J., and Lee, G.B. (2015). A microfluidic system integrated with buried optical fibers for detection of Phalaenopsis orchid pathogens. Biosens. Bioelectron.10.1016/j.bios.2014.08.013 ↗
20. Chapter nine—Methods for cell and particle tracking10.1016/B978-0-12-391857-4.00009-4 ↗
21. A survey for the applications of content-based microscopic image analysis in microorganism classification domains10.1007/s10462-017-9572-4 ↗
22. Kis, B. (2019, January 3–5). Counting Bacteria Colonies Based on Image Processing Methods. Proceedings of the Medical Technologies Congress (TIPTEKNO), Selçuk, Turkey.10.1109/TIPTEKNO.2019.8895213 ↗
23. Bonteanu, P. (2019, January 23–26). A new pupil detection algorithm based on circular Hough transform approaches. Proceedings of the IEEE 25th International Symposium for Design and Technology in Electronic Packaging, Cluj-Napoca, Romania.10.1109/SIITME47687.2019.8990887 ↗