DIY CD Spectrometer Urine Strip Test

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DIY CD Spectrometer Urine Strip Test

ISEF Category: Biomedical Engineering

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Subcategory: Biomedical Sensors and Imaging  ·  Difficulty: Intermediate  ·  Setup: Home Setup  ·  Time: 1 to 2 Months

The Hook

Pharmacy urine strips give qualitative answers like positive or negative. A real lab gives concentrations. A compact-disc diffraction grating taped to a smartphone closes the gap. With ML correction for ambient light, a 5-dollar spectrometer reads glucose, protein, and ketone bands with lab-comparable accuracy.

What Is It?

A compact disc has microscopic grooves that act as a diffraction grating. Pointing a phone camera through a piece of CD splits white light into a spectrum.

Urine reagent strips change color in response to specific analytes. Glucose, protein, and ketone bands each absorb a different part of the spectrum. Reading absorbance peaks gives concentration estimates.

Ambient light is the enemy of color reading. A small ML model trained on labeled spectra under different lighting corrects for that variability and outputs a concentration even in mixed light.

Why This Is a Good Topic

Low-cost diagnostics is an active research field. The equipment is paperclip-level cheap. You will learn spectroscopy, color calibration, and ML correction.

Research Questions

  • How does spectrometer slit width change peak resolution?
  • What is the effect of ambient light on prediction error?
  • Does the ML correction beat a fixed-illuminant baseline?
  • To what extent does reagent-strip brand affect transferability?
  • Which analyte has the lowest detection limit?
  • How does camera exposure shift apparent absorbance?
  • What is the effect of training-set size on correction accuracy?

Basic Materials

  • Old CD or DVD (used as grating).
  • 3D-printed or cardboard spectrometer housing.
  • Smartphone.
  • Standard urine reagent strips.
  • Known concentration standards (glucose solutions).
  • LED light source.

Advanced Materials

  • Lab spectrophotometer for ground truth.
  • Calibrated wavelength reference lamp.
  • Clinical urinalyzer access.
  • Cloud GPU.

Software & Tools

  • Python (NumPy and SciPy): Processes spectra.
  • OpenCV: Extracts diffraction lines from images.
  • scikit-learn: Trains the ambient-light correction model.
  • Matplotlib: Plots calibration curves.

Experiment Steps

  1. Build the spectrometer housing and lock geometry.
  2. Calibrate wavelengths using a known LED or fluorescent lamp.
  3. Build per-analyte calibration curves under fixed lighting.
  4. Train the ML correction across varied lighting.
  5. Compare predictions vs. a clinical analyzer.
  6. Report agreement across analytes and lighting.

Common Pitfalls

  • Reading absorbance from saturated pixels.
  • Skipping wavelength calibration between sessions.
  • Mixing reagent-strip brands without re-training.
  • Reporting peak height without integration.
  • Ignoring time-after-dip variability.

What Makes This Competitive

Run analyte-specific calibration curves with at least five concentrations and triplicate strips. Compare your readings to a clinical urinalyzer and report Bland-Altman agreement. Audit performance across lighting conditions and reagent-strip brands.

Project Variations

  • Use a transmission grating from a craft store instead of a CD.
  • Add saliva analyte detection.
  • Combine with smartphone bilirubin imaging for a multi-test platform.

Learn More

  • PubMed: Search smartphone urine analysis reviews.
  • NIH PubMed Central: Open-access spectrophotometry papers.
  • OpenCV documentation: Free imaging tutorials.
  • Public Lab spectrometry kits: Free DIY guides.
  • MIT OpenCourseWare: Course 5.33 Advanced Chemical Experimentation.
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