Effect of smartphone camera settings in colorimetric measurements under controlled illumination

Thakur, Ritambhara; Bhatt, Sunita; Dubey, Swapnil

doi:10.1109/cisp-bmei53629.2021.9624389

Cited by 5 publications

(3 citation statements)

References 21 publications

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“…Again, relying on the benefits of smartphones, some researchers have developed supporting artificial intelligence techniques to replace human judgment, enabling prompt generation of test results [24][25][26]. However, due to the limitations of smartphones and development platforms, most of these studies still rely on image sensors for urine composition analysis [27,28].…”

Section: Urinalysis Based On Image Sensorsmentioning

confidence: 99%

Dipstick color recognition in dry chemical urinalysis: A mini review

Xu,

Yan,

et al. 2023

PMD

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Urinalysis is an essential diagnostic tool for urinary tract infections, kidney disease, diabetes, and other clinical conditions. Dipsticks, which allow for quick screening of urine specimens, are used in the clinic settings to identify the presence and concentration of labeled substances such as urine pH, urine protein, urine glucose, urine ketone, and urine nitrite. This paper reviews four urine dry chemical analysis methods, which are based on human eyes, integrating sphere, color sensors, and image sensors, respectively. The techniques of each method are also discussed.

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Section: Urinalysis Based On Image Sensorsmentioning

confidence: 99%

Dipstick color recognition in dry chemical urinalysis: A mini review

Xu,

Yan,

et al. 2023

PMD

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“…Most prior works largely depended on post-processing after allowing the complex camera system to automatically capture a video, with autoexposure, auto-white balancing, and video compression algorithms altering the raw signal in non-linear ways (4,6,(20)(21)(22)(23)(24)(25)(26)(27)(28). Only a handful of works have addressed changing exposure by disabling auto-exposure (29)(30)(31); calculating absorption frameby-frame in an online manner to avoid compression; attempting to control white balance by designating a preset, most commonly an incandescent setting to emphasize blue and green channels (32)(33)(34); or opting to control each color channels with individual gain settings (8,11). Although these works hint at the right direction in addressing the issues, our investigation finds that these solutions are inadequate, and in fact, overlook some of the most crucial camera parameters affecting cPPG measurements.…”

Section: Introductionmentioning

confidence: 99%

A calibration method for smartphone camera photophlethysmography

Xuan,

Barry,

Antipa

et al. 2023

Front. Digit. Health

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Smartphone camera photoplethysmography (cPPG) enables non-invasive pulse oximetry and hemoglobin concentration measurements. However, the aesthetic-driven non-linearity in default image capture and preprocessing pipelines poses challenges for consistency and transferability of cPPG across devices. This work identifies two key parameters—tone mapping and sensor threshold—that significantly impact cPPG measurements. We propose a novel calibration method to linearize camera measurements, thus enhancing consistency and transferability of cPPG across devices. A benchtop calibration system is also presented, leveraging a microcontroller and LED setup to characterize these parameters for each phone model. Our validation studies demonstrate that, with appropriate calibration and camera settings, cPPG applications can achieve 74% higher accuracy than with default settings. Moreover, our calibration method proves effective across different smartphone models (N=4), and calibrations performed on one phone can be applied to other smartphones of the same model (N=6), enhancing consistency and scalability of cPPG applications.

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“…Image quality can suffer from non-uniformity and non-reproducibility, which negatively affects the accuracy of the measurements. To obtain good measurements, some strategies, such as the use of boxes with light [ 20 ] or using the light of the phone, have been proposed to eliminate interference from ambient light [ 21 ]. Depending on the type of light, alternative color temperature can be observed, and additionally, different information in certain wavelength ranges can be provided by each type of light.…”

Section: Introductionmentioning

confidence: 99%

Advances in the Measurement of Polymeric Colorimetric Sensors Using Portable Instrumentation: Testing the Light Influence

et al. 2022

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Sustainable and green sensors based on polydimethyl siloxane (PDMS) or cellulose polymers, as a case of study of the use of portable instrumentation joined to a smartphone, have been tested. A smartphone camera was used to obtain images and was also coupled to a minispectrometer, without and with an optical fiber probe to register spectra. To study light influence on the analytical signal, light-emitting diode (LED), halogen light and daylight have been assayed. A corrective palette of 24 colors and a set with 45 colors from different color ranges were used as the validation set. The results indicated that halogen light was the best option to obtain the spectra. However, for digital image analysis, it was the LED light that gave a greater approximation of the RGB values of the real colors. Based on these results, the spectra and the RGB components of PDMS solid sensors doped with 1,2-naphtoquinone-4-sulfonate (NQS) for the determination of ammonium in water or urea in urine, PDMS doped with Griess reagent for developing the assay of nitrite in waters and cellulose sensors for the determination of hydrogen sulfide in the atmospheres have been obtained. The results achieved were good in terms of sensitivity and linearity and were comparable to those obtained using a laboratory benchtop instrument. Several rules for selecting the most suitable light source to obtain the spectra and/or images have been established and an image correction method has been introduced.

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Effect of smartphone camera settings in colorimetric measurements under controlled illumination

Cited by 5 publications

References 21 publications

Dipstick color recognition in dry chemical urinalysis: A mini review

Dipstick color recognition in dry chemical urinalysis: A mini review

A calibration method for smartphone camera photophlethysmography

Advances in the Measurement of Polymeric Colorimetric Sensors Using Portable Instrumentation: Testing the Light Influence

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