Recent Trends in Smartphone-based Detection for Biomedical Applications: a Review

Overview

Journal Anal Bioanal Chem

Specialty Chemistry

Date 2021 Feb 15

PMID 33586007

Citations 31

Authors

Soumyabrata Banik

Sindhoora Kaniyala Melanthota

Arbaaz

Joel Markus Vaz

Vishak Madhwaraj Kadambalithaya

Iftak Hussain

Sibasish Dutta

Nirmal Mazumder

Affiliations

Soon will be listed here.

Abstract

Smartphone-based imaging devices (SIDs) have shown to be versatile and have a wide range of biomedical applications. With the increasing demand for high-quality medical services, technological interventions such as portable devices that can be used in remote and resource-less conditions and have an impact on quantity and quality of care. Additionally, smartphone-based devices have shown their application in the field of teleimaging, food technology, education, etc. Depending on the application and imaging capability required, the optical arrangement of the SID varies which enables them to be used in multiple setups like bright-field, fluorescence, dark-field, and multiple arrays with certain changes in their optics and illumination. This comprehensive review discusses the numerous applications and development of SIDs towards histopathological examination, detection of bacteria and viruses, food technology, and routine diagnosis. Smartphone-based devices are complemented with deep learning methods to further increase the efficiency of the devices. Graphical Abstract.

Citing Articles

Smartphone conjunctiva photography for malaria risk stratification in asymptomatic school age children.

Hong S, Park S, Kwon S, Sakthivel H, Nagappa S, Leem J NPJ Digit Med. 2025; 8(1):151.

PMID: 40065117 PMC: 11893748. DOI: 10.1038/s41746-025-01548-8.

Single-cell pathogen diagnostics for combating antibiotic resistance.

Li H, Hsieh K, Wong P, Mach K, Liao J, Wang T Nat Rev Methods Primers. 2025; 3.

PMID: 39917628 PMC: 11800871. DOI: 10.1038/s43586-022-00190-y.

Impact of Point-of-Care Testing on Diagnosis, Treatment, and Surveillance of Vaccine-Preventable Viral Infections.

Lakshmanan K, Liu B Diagnostics (Basel). 2025; 15(2).

PMID: 39857007 PMC: 11763637. DOI: 10.3390/diagnostics15020123.

AlkaPhos: a novel fluorescent probe as a potential point-of-care diagnostic tool to estimate recurrence risk of meningiomas.

Hemmer S, Hui X, Draeger J, Menges J, Schwarz E, Wrede A Neurosurg Rev. 2025; 48(1):27.

PMID: 39775316 PMC: 11706915. DOI: 10.1007/s10143-024-03172-8.

A New Caffeine Detection Method Using a Highly Multiplexed Smartphone-Based Spectrometer.

Zhuo E, Xia H, Hu H, Lin Y Biosensors (Basel). 2024; 14(12).

PMID: 39727855 PMC: 11674217. DOI: 10.3390/bios14120590.

References

Tian B, Qiu Z, Ma J, Zardan Gomez de la Torre T, Johansson C, Svedlindh P . Attomolar Zika virus oligonucleotide detection based on loop-mediated isothermal amplification and AC susceptometry. Biosens Bioelectron. 2016; 86:420-425. DOI: 10.1016/j.bios.2016.06.085. View

Olthoff K, Kulik L, Samstein B, Kaminski M, Abecassis M, Emond J . Validation of a current definition of early allograft dysfunction in liver transplant recipients and analysis of risk factors. Liver Transpl. 2010; 16(8):943-9. DOI: 10.1002/lt.22091. View

Liang P, Park T, Yoon J . Rapid and reagentless detection of microbial contamination within meat utilizing a smartphone-based biosensor. Sci Rep. 2014; 4:5953. PMC: 4121612. DOI: 10.1038/srep05953. View

Ojha A, Banik S, Kaniyala Melanthota S, Mazumder N . Light emitting diode (LED) based fluorescence microscopy for tuberculosis detection: a review. Lasers Med Sci. 2020; 35(6):1431-1437. DOI: 10.1007/s10103-019-02947-6. View

Ludwig S, Smits N, van der Veer G, Bremer M, Nielen M . Multiple protein biomarker assessment for recombinant bovine somatotropin (rbST) abuse in cattle. PLoS One. 2013; 7(12):e52917. PMC: 3531382. DOI: 10.1371/journal.pone.0052917. View

Landers T, Cohen B, Wittum T, Larson E . A review of antibiotic use in food animals: perspective, policy, and potential. Public Health Rep. 2012; 127(1):4-22. PMC: 3234384. DOI: 10.1177/003335491212700103. View

Masawat P, Harfield A, Namwong A . An iPhone-based digital image colorimeter for detecting tetracycline in milk. Food Chem. 2015; 184:23-9. DOI: 10.1016/j.foodchem.2015.03.089. View

Martinez A, Phillips S, Wiley B, Gupta M, Whitesides G . FLASH: a rapid method for prototyping paper-based microfluidic devices. Lab Chip. 2008; 8(12):2146-50. PMC: 3065062. DOI: 10.1039/b811135a. View

Ah Lee S, Yang C . A smartphone-based chip-scale microscope using ambient illumination. Lab Chip. 2014; 14(16):3056-63. PMC: 4124038. DOI: 10.1039/c4lc00523f. View

10.

Priye A, Bird S, Light Y, Ball C, Negrete O, Meagher R . A smartphone-based diagnostic platform for rapid detection of Zika, chikungunya, and dengue viruses. Sci Rep. 2017; 7:44778. PMC: 5357913. DOI: 10.1038/srep44778. View

11.

Wu Y, Shiledar A, Li Y, Wong J, Feng S, Chen X . Air quality monitoring using mobile microscopy and machine learning. Light Sci Appl. 2018; 6(9):e17046. PMC: 6062327. DOI: 10.1038/lsa.2017.46. View

12.

Yang K, Peretz-Soroka H, Liu Y, Lin F . Novel developments in mobile sensing based on the integration of microfluidic devices and smartphones. Lab Chip. 2016; 16(6):943-58. PMC: 5142836. DOI: 10.1039/c5lc01524c. View

13.

Boehme C, Nabeta P, Hillemann D, Nicol M, Shenai S, Krapp F . Rapid molecular detection of tuberculosis and rifampin resistance. N Engl J Med. 2010; 363(11):1005-15. PMC: 2947799. DOI: 10.1056/NEJMoa0907847. View

14.

Thom N, Lewis G, Yeung K, Phillips S . Quantitative Fluorescence Assays Using a Self-Powered Paper-Based Microfluidic Device and a Camera-Equipped Cellular Phone. RSC Adv. 2014; 4(3):1334-1340. PMC: 3904390. DOI: 10.1039/C3RA44717K. View

15.

Bornhorst J, Nustede E, Fudickar S . Mass Surveilance of -Smartphone-Based DIY Microscope and Machine-Learning-Based Approach for Worm Detection. Sensors (Basel). 2019; 19(6). PMC: 6471353. DOI: 10.3390/s19061468. View

16.

Cesaretti M, Pote N, Dondero F, Cauchy F, Schneck A, Soubrane O . Testing feasibility of an accurate microscopic assessment of macrovesicular steatosis in liver allograft biopsies by smartphone add-on lenses. Microsc Res Tech. 2017; 81(1):58-63. DOI: 10.1002/jemt.22956. View

17.

Park T, Li W, McCracken K, Yoon J . Smartphone quantifies Salmonella from paper microfluidics. Lab Chip. 2013; 13(24):4832-40. DOI: 10.1039/c3lc50976a. View

18.

Gurcan M, Boucheron L, Can A, Madabhushi A, Rajpoot N, Yener B . Histopathological image analysis: a review. IEEE Rev Biomed Eng. 2010; 2:147-71. PMC: 2910932. DOI: 10.1109/RBME.2009.2034865. View

19.

Ozcan A . Mobile phones democratize and cultivate next-generation imaging, diagnostics and measurement tools. Lab Chip. 2014; 14(17):3187-94. PMC: 4117730. DOI: 10.1039/c4lc00010b. View

20.

Ganguli A, Ornob A, Yu H, Damhorst G, Chen W, Sun F . Hands-free smartphone-based diagnostics for simultaneous detection of Zika, Chikungunya, and Dengue at point-of-care. Biomed Microdevices. 2017; 19(4):73. DOI: 10.1007/s10544-017-0209-9. View