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Development of a smartphone based spectrometer for high-resolution urinalysis
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  • Open access
  • Published: 12 February 2026

Development of a smartphone based spectrometer for high-resolution urinalysis

  • Kefan Song1,2,
  • Ilan Mandel3,
  • Jason Cobb4,
  • Tanzeem Choudhury3 &
  • …
  • Alexander T. Adams2,5,6,7 

Scientific Reports , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Biomarkers
  • Diseases
  • Health care
  • Medical research
  • Nephrology

Abstract

Chronic kidney disease (CKD) affects millions worldwide but remains under-diagnosed, especially in resource-limited settings. Current diagnostic methods, including visual and dipstick urinalysis, lack quantitative accuracy, while laboratory-based tests remain inaccessible for routine or remote monitoring. Here we present SpectraPhone, a smartphone-integrated, portable spectrometer designed for quantitative, point-of-care urinalysis. Leveraging the smartphone’s built-in camera and flashlight, SpectraPhone captures high-resolution spectral data to accurately quantify hematuria and albuminuria, which are both biomarkers of CKD. Through rigorous optical characterization and empirical validation, SpectraPhone demonstrates superior quantification performance, accurately measuring red blood cell concentrations (\(R^2\) = 0.9913, RMSE = 61.6086 RBC/\(\upmu\)L, MAE = 43.9077 RBC/\(\upmu\)L) and albumin levels (\(R^2\) = 0.9981, RMSE = 11.8525 mg/dL, MAE = 8.4985 mg/dL), significantly surpassing the capabilities of conventional qualitative methods. With the addition of bromophenol blue reagent, SpectraPhone achieves more accurate urine albumin measurements (\(R^2\) = 0.9997, RMSE = 4.2583 mg/dL, MAE = 3.2625 mg/dL), enabling clinical-grade albuminuria detection. SpectraPhone’s affordability, ease of use, and robust performance highlight its potential to transform routine CKD screening, facilitate early detection, improve disease management, and increase healthcare access globally.

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Data availability

Data that support the finding of this study can be accessed from https://github.com/Uncommon-Sense-Lab/SpectraPhone.git.

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Funding

No external funding was received for this study.

Author information

Authors and Affiliations

  1. Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA

    Kefan Song

  2. Institute of Robotics and Intelligent Systems, Georgia Institute of Technology, Atlanta, GA, 30332, USA

    Kefan Song & Alexander T. Adams

  3. Information Science, Cornell Tech, New York, NY, 10044, USA

    Ilan Mandel & Tanzeem Choudhury

  4. Renal Medicine, Emory University School of Medicine, Atlanta, GA, 30318, USA

    Jason Cobb

  5. School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA, 30332, USA

    Alexander T. Adams

  6. Parker H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA

    Alexander T. Adams

  7. Institute of People and Technology, Georgia Institute of Technology, Atlanta, GA, 30332, USA

    Alexander T. Adams

Authors
  1. Kefan Song
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  2. Ilan Mandel
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  3. Jason Cobb
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  4. Tanzeem Choudhury
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  5. Alexander T. Adams
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Contributions

A.T.A. and T.C. proposed and supervised the project. A.T.A. designed and built the system. K.S. and A.T.A. performed the experiments. K.S. and A.T.A. designed the figures and illustrations. K.S. and A.T.A. performed the data analyses. K.S., I.M., J.C., and A.T.A. wrote the manuscript.

Corresponding author

Correspondence to Kefan Song.

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The authors declare no competing interests.

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Cite this article

Song, K., Mandel, I., Cobb, J. et al. Development of a smartphone based spectrometer for high-resolution urinalysis. Sci Rep (2026). https://doi.org/10.1038/s41598-026-38307-y

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  • Received: 07 August 2025

  • Accepted: 29 January 2026

  • Published: 12 February 2026

  • DOI: https://doi.org/10.1038/s41598-026-38307-y

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Keywords

  • Chronic kidney disease
  • Mobile spectroscopy
  • Urine testing
  • Hematuria
  • Albuminuria
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