StripSense: A Low-Cost Raspberry Pi Grayscale Reader for Urine Reagent Strips—Design, Operational Verification, and Literature Comparison

Reading urine reagent strips against a printed chart is subjective and depends on lighting, viewing angle and reading time. This paper presents StripSense, a student prototype that removes these factors with a light-tight enclosure, ten white LEDs, a Raspberry Pi 5 and Pi HQ camera. Each of the ten pads is read at its own chart time, reduced to one mean grayscale value, and mapped to analyte-specific chart references by linear interpolation; the touch screen shows the value, unit and nearest chart level. In an operational verification with a commercial control solution (one level, one strip lot, three runs), the device ran continuously on the official 5.1 V/5 A supply, completed all ten pads in every run, and reported values matching the control’s labelled levels for 10/10 pads. Three alternative power sources failed. We state plainly what this evidence does not show: no multi-level accuracy, no coefficient of variation, and no sensitivity or specificity have been measured. The design is compared with five published systems. StripSense is not a medical device and must not be used for diagnosis.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-30
DOI
https://doi.org/10.5281/zenodo.23813208
Primary Topic
Biosensors and Analytical Detection
Type
preprint
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preprint

StripSense: A Low-Cost Raspberry Pi Grayscale Reader for Urine Reagent Strips—Design, Operational Verification, and Literature Comparison

Ninad Mehendale, Gayatri Vaidya, Jaiee Paradkar, Jiya Parsana
Zenodo (CERN European Organization for Nuclear Research)
Biosensors and Analytical Detection
preprint

StripSense: A Low-Cost Raspberry Pi Grayscale Reader for Urine Reagent Strips—Design, Operational Verification, and Literature Comparison

Ninad Mehendale, Gayatri Vaidya, Jaiee Paradkar, Jiya Parsana
preprint en

Abstract

Reading urine reagent strips against a printed chart is subjective and depends on lighting, viewing angle and reading time. This paper presents StripSense, a student prototype that removes these factors with a light-tight enclosure, ten white LEDs, a Raspberry Pi 5 and Pi HQ camera. Each of the ten pads is read at its own chart time, reduced to one mean grayscale value, and mapped to analyte-specific chart references by linear interpolation; the touch screen shows the value, unit and nearest chart level. In an operational verification with a commercial control solution (one level, one strip lot, three runs), the device ran continuously on the official 5.1 V/5 A supply, completed all ten pads in every run, and reported values matching the control’s labelled levels for 10/10 pads. Three alternative power sources failed. We state plainly what this evidence does not show: no multi-level accuracy, no coefficient of variation, and no sensitivity or specificity have been measured. The design is compared with five published systems. StripSense is not a medical device and must not be used for diagnosis.

Zenodo (CERN European Organization for Nuclear Research)
Somaiya Vidyavihar University (IN)
Biosensors and Analytical Detection
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