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A smartphone-based calibration-free portable urinalysis device

基于智能手机的免校准便携式尿液分析设备

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Abstract

As one of the most common medical diagnosis methods, urinalysis is a highly demanded technique for screening tests or daily monitoring of various diseases. With the rapid development of POC (point-of-care) systems, a convenient house-using urinalysis device is widely needed. However, considering the difference of onboard systems and multiple test indicators in urinalysis, the design of such an intelligent device is still challenging. In this paper, a smartphone-based portable urinalysis system has been developed and applied for the colorimetric analysis of routine urine examination indices using an Android app. By integrating the test paper sensor in the portable device for urinalysis, our system significantly improves the instability of conventional dipstick-based manual colorimetry, and the smartphone application used for color discrimination enhances the accuracy of the visual assessment of sample strips. Using a simple operation approach that takes ∼ 2 min per test, our system can be applied as rapid urinalysis for routine check-ups.

摘要

作为最常见的医学诊断方法, 尿液分析是一种用于筛查测试或日常监测各种疾病的高需求技术。随着POC (point-of-care) 即时医疗系统的快速发展, 人们广泛需要一种方便的家用尿液分析设备。然而, 考虑到机载系统的差异以及尿液分析中的多项测试指标, 这样智能设备的设计仍然具有挑战性。在本文中, 开发了一种基于智能手机的便携式尿液分析系统, 并将其应用于Android 程序进行尿液常规检查中的指标比色分析。通过在便携式尿液分析设备中集成试纸传感器, 我们的系统显着改善了传统基于试纸的手动比色法的不稳定性, 用于颜色辨别的智能手机应用程序提高了样品条视觉评估的准确性。以简单的操作方法和每次约2 min 的测试, 我们的系统可应用于尿液的常规检查和快速分析。

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References

  1. BIKBOV B, PURCELL C A, LEVEY A S, et al. Global, regional, and national burden of chronic kidney disease, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017 [J]. The Lancet, 2020, 395: 709–733. DOI: https://doi.org/10.1016/S0140-6736(20)30045-3.

    Article  Google Scholar 

  2. WEBSTER A C, NAGLER E V, MORTON R L, MASSON P. Chronic kidney disease [J]. The Lancet, 2017, 389(10075): 1238–1252. DOI: https://doi.org/10.1016/S0140-6736(16)32064-5.

    Article  Google Scholar 

  3. RULE A D, LARSON T S, BERGSTRALH E J, SLEZAK J M, JACOBSEN S J, COSIO F G. Using serum creatinine to estimate glomerular filtration rate: Accuracy in good health and in chronic kidney disease [J]. Annals of Internal Medicine, 2004, 141(12): 929. DOI: https://doi.org/10.7326/0003-4819-14112-200412210-00009.

    Article  Google Scholar 

  4. KRAMER H, MOLITCH M E. Screening for kidney disease in adults with diabetes [J]. Diabetes Care, 2005, 28(7): 1813–1816. DOI: https://doi.org/10.2337/diacare.28.7.1813.

    Article  Google Scholar 

  5. YAMAGATA K, ISEKI K, NITTA K, IMAI H, IINO Y, MATSUO S, MAKINO H, HISHIDA A. Chronic kidney disease perspectives in Japan and the importance of urinalysis screening [J]. Clinical and Experimental Nephrology, 2008, 12(1): 1–8. DOI: https://doi.org/10.1007/s10157-007-0010-9.

    Article  Google Scholar 

  6. SIMERVILLE J A, MAXTED W C, PAHIRA J J. Urinalysis: A comprehensive review [J]. American Family Physician, 2005, 71(6): 1153–1162.

    Google Scholar 

  7. RA M, MUHAMMAD M S, LIM C, HAN Se-hui, JUNG C, KIM W Y. Smartphone-based point-of-care urinalysis under variable illumination [J]. IEEE Journal of Translational Engineering in Health and Medicine, 2018, 6: 1–11. DOI: https://doi.org/10.1109/JTEHM.2017.2765631.

    Article  Google Scholar 

  8. XIANG Ji-wen, ZHANG Yong, CAI Zi-liang, WANG Wan-jun, WANG Cai-feng. A 3D printed centrifugal microfluidic platform for automated colorimetric urinalysis [J]. Microsystem Technologies, 2020, 26(2): 291–299. DOI: https://doi.org/10.1007/s00542-019-04709-4.

    Article  Google Scholar 

  9. YANG R, CHENG W, CHEN X, QIAN Q, ZHANG Q, PAN Y, DUAN P, MIAO P. Color space transformation-based smartphone algorithm for colorimetric urinalysis [J]. ACS Omega, 2018, 3(9): 12141–12146. DOI: https://doi.org/10.1021/acsomega.8b01270.

    Article  Google Scholar 

  10. GUBALA V, HARRIS L F, RICCO A J, TAN M X, WILLIAMS D E. Point of care diagnostics: Status and future [J]. Analytical Chemistry, 2012, 84(2): 487–515. DOI: https://doi.org/10.1021/ac2030199.

    Article  Google Scholar 

  11. ZHANG Di-ming, LU Yan-li, ZHANG Qian, LIU Lei, LI Shuang, YAO Yao, JIANG Jing, LIU G L, LIU Qing-jun. Protein detecting with smartphone-controlled electrochemical impedance spectroscopy for point-of-care applications [J]. Sensors and Actuators B: Chemical, 2016, 222: 994–1002. DOI: https://doi.org/10.1016/j.snb.2015.09.041.

    Article  Google Scholar 

  12. LIAO S C, PENG Jing, MAUK M G, AWASTHI S, SONG Jin-zhao, FRIEDMAN H, BAU H H, LIU Chang-chun. Smart cup: A minimally-instrumented, smartphone-based point-of-care molecular diagnostic device [J]. Sensors and Actuators B: Chemical, 2016, 229: 232–238. DOI: https://doi.org/10.1016/j.snb.2016.01.073.

    Article  Google Scholar 

  13. BERG B, CORTAZAR B, TSENG D, OZKAN H, FENG S, WEI Q, CHAN R Y, BURBANO J, FAROOQUI Q, et al. Cellphone-based hand-held microplate reader for point-of-care testing of enzyme-linked immunosorbent assays [J]. ACS Nano, 2015, 9(8): 7857–7866. DOI: https://doi.org/10.1021/acsnano.5b03203.

    Article  Google Scholar 

  14. YOU Min-li, LIN Min, GONG Yan, WANG Shu-rui, LI Ang, JI Ling-yu, ZHAO Hao-xiang, LING Kai, WEN Ting, et al. Household fluorescent lateral flow strip platform for sensitive and quantitative prognosis of heart failure using dual-color upconversion nanoparticles [J]. ACS Nano, 2017, 11(6): 6261–6270. DOI: https://doi.org/10.1021/acsnano.7b02466.

    Article  Google Scholar 

  15. XU Xia-yu, AKAY A, WEI Hui-lin, WANG Shu-qi, PINGGUAN-MURPHY B, ERLANDSSON B E, LI Xiu-jun, LEE W, HU Jie, et al. Advances in smartphone-based point-of-care diagnostics [J]. Proceedings of the IEEE, 2015, 103(2): 236–247. DOI: https://doi.org/10.1109/JPROC.2014.2378776.

    Article  Google Scholar 

  16. XU Zhen-zhen, LIU Zi-jian, XIAO Meng, JIANG Le-lun, YI Chang-qing. A smartphone-based quantitative point-of-care testing (POCT) system for simultaneous detection of multiple heavy metal ions [J]. Chemical Engineering Journal, 2020, 394: 124966. DOI: https://doi.org/10.1016/j.cej.2020.124966.

    Article  Google Scholar 

  17. MOONRUNGSEE N, PENCHAREE S, JAKMUNEE J. Colorimetric analyzer based on mobile phone camera for determination of available phosphorus in soil [J]. Talanta, 2015, 136: 204–209. DOI: https://doi.org/10.1016/j.talanta.2015.01.024.

    Article  Google Scholar 

  18. SHEN Li, HAGEN J A, PAPAUTSKY I. Point-of-care colorimetric detection with a smartphone [J]. Lab on a Chip, 2012, 12(21): 4240–4243. DOI: https://doi.org/10.1039/C2LC40741H.

    Article  Google Scholar 

  19. SAFAVIEH M, AHMED M U, SOKULLU E, NG A, BRAESCU L, ZOUROB M. A simple cassette as point-of-care diagnostic device for naked-eye colorimetric bacteria detection [J]. The Analyst, 2014, 139(2): 482–487. DOI: https://doi.org/10.1039/c3an01859h.

    Article  Google Scholar 

  20. KIM H, AWOFESO O, CHOI S, JUNG Y, BAE E. Colorimetric analysis of saliva — alcohol test strips by smartphone-based instruments using machine-learning algorithms [J]. Applied Optics, 2016, 56(1): 84. DOI: https://doi.org/10.1364/ao.56.000084.

    Article  Google Scholar 

  21. COSKUN A F, NAGI R, SADEGHI K, PHILLIPS S, OZCAN A. Albumin testing in urine using a smart-phone [J]. Lab on a Chip, 2013, 13(21): 4231–4238. DOI: https://doi.org/10.1039/c3lc50785h.

    Article  Google Scholar 

  22. LAI T S, CHANG Ting-chou, WANG S C. Gold nanoparticle-based colorimetric methods to determine protein contents in artificial urine using membrane micro-concentrators and mobile phone camera [J]. Sensors and Actuators B: Chemical, 2017, 239: 9–16. DOI: https://doi.org/10.1016/j.snb.2016.07.158.

    Article  Google Scholar 

  23. JALAL U M, JIN G J, SHIM J S. Paper-plastic hybrid microfluidic device for smartphone-based colorimetric analysis of urine [J]. Analytical Chemistry, 2017, 89(24): 13160–13166. DOI: https://doi.org/10.1021/acs.analchem.7b02612.

    Article  Google Scholar 

  24. CHAN H N, SHU Yi-wei, XIONG Bin, CHEN Yang-fan, CHEN Yin, TIAN Qian, MICHAEL S A, SHEN Bo, WU Hong-kai. Simple, cost-effective 3D printed microfluidic components for disposable, point-of-care colorimetric analysis [J]. ACS Sensors, 2016, 1(3): 227–234. DOI: https://doi.org/10.1021/acssensors.5b00100.

    Article  Google Scholar 

  25. SOLMAZ M E, MUTLU A Y, ALANKUS G, KILIÇ V, BAYRAM A, HORZUM N. Quantifying colorimetric tests using a smartphone app based on machine learning classifiers [J]. Sensors and Actuators B: Chemical, 2018, 255: 1967–1973. DOI: https://doi.org/10.1016/j.snb.2017.08.220.

    Article  Google Scholar 

  26. YE Jian-cheng, LI Nan, LU Ying, CHENG Jing, XU You-chun. A portable urine analyzer based on colorimetric detection [J]. Analytical Methods, 2017, 9(16): 2464–2471. DOI: https://doi.org/10.1039/c7ay00780a.

    Article  Google Scholar 

  27. HE Xue-cheng, PEI Quan-bing, XU Tai-lin, ZHANG Xue-ji. Smartphone-based tape sensors for multiplexed rapid urinalysis [J]. Sensors and Actuators B: Chemical, 2020, 304: 127415. DOI: https://doi.org/10.1016/j.snb.2019.127415.

    Article  Google Scholar 

  28. TANAKA R, YUHI T, NAGATANI N, ENDO T, KERMAN K, TAKAMURA Y, TAMIYA E. A novel enhancement assay for immunochromatographic test strips using gold nanoparticles [J]. Analytical and Bioanalytical Chemistry, 2006, 385(8): 1414–1420. DOI: https://doi.org/10.1007/s00216-006-0549-4.

    Article  Google Scholar 

Download references

Funding

Projects(61922093, U1813211) supported by the National Natural Science Foundation of China; Projects (SGDX20201103093003017, JCYJ20200109114827177) supported by Shenzhen Key Basic Research Project, China

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Correspondence to Ya-jing Shen  (申亚京).

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Contributors

GUO Dong and SHEN Ya-jing provided the concept. GUO Dong and LI Gen conducted the literature review and wrote the first draft of the manuscript. GUO Dong and MIAO Jia-qi analyzed the measured data. All authors replied to reviewers’ comments and revised the final version.

Conflict of interest

GUO Dong, LI Gen, MIAO Jia-qi, and SHEN Ya-jing declare that they have no conflict of interest.

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Guo, D., Li, G., Miao, Jq. et al. A smartphone-based calibration-free portable urinalysis device. J. Cent. South Univ. 28, 3829–3837 (2021). https://doi.org/10.1007/s11771-021-4883-7

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  • DOI: https://doi.org/10.1007/s11771-021-4883-7

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