Accurate device-independent colorimetric measurements using smartphones

Artificial Intelligence in Diagnostics: Enhancing Urine Test Accuracy Using a Mobile Phone-Based Reading System

Background

Urinalysis, an essential diagnostic tool, faces challenges in terms of standardization and accuracy. The use of artificial intelligence (AI) with mobile technology can potentially solve these challenges. Therefore, we investigated the effectiveness and accuracy of an AI-based program in automatically interpreting urine test strips using mobile phone cameras, an approach that may revolutionize point-of-care testing.

Methods

We developed novel urine test strips and an AI algorithm for image capture. Sample images from the Chungnam National University Sejong Hospital were collected to train a k-nearest neighbor classification algorithm to read the strips. A mobile application was developed for image capturing and processing. We assessed the accuracy, sensitivity, specificity, and ROC area under the curve for 10 parameters.

Results

In total, 2,612 urine test strip images were collected. The AI algorithm demonstrated 98.7% accuracy in detecting urinary nitrite and 97.3% accuracy in detecting urinary glucose. The sensitivity and specificity were high for most parameters. However, this system could not reliably determine the specific gravity. The optimal time for capturing the test strip results was 75 secs after dipping.

Conclusions

The AI-based program accurately interpreted urine test strips using smartphone cameras, offering an accessible and efficient method for urinalysis. This system can be used for immediate analysis and remote testing. Further research is warranted to refine test parameters such as specific gravity to enhance accuracy and reliability.

Diagnosing anaemia via smartphone colorimetry of the eye in a population of pregnant women

Objective.Screening for disease using a smartphone camera is an emerging tool for conditions such as jaundice and anaemia, which are associated with a colour change (yellowing in jaundice; pallor in anaemia) of the external tissues. Based on this, we aimed to test a technique to non-invasively screen for anaemia in a population highly affected by anaemia: pregnant women in India. In this group, anaemia can have severe health consequences for both the mother and child.Approach.Over 3 years of data collection, in 486 pregnant women in India, we attempted to replicate a previously successful smartphone imaging technique to screen for anaemia. Using smartphone images of the eye and eyelid, we compared two techniques (white balancing and ambient subtraction) to control for variation in ambient lighting, and then extracted 'redness' features from images, which we used as features to predict anaemia via statistical modelling.Main results.We found that we were not able to predict anaemia with enough accuracy to be clinically useful, at 89.6% sensitivity and 26.1% specificity. We consider the hypothesis that this may be due to pigmentation on the sclera and palpebral conjunctiva. Visual judgement showed that pigmentation on the sclera, which may affect the measured colour, is more prevalent in pregnant women in India than in preschool aged children in Ghana (a population previously studied in this context). When participants with subjectively judged visible scleral pigmentation are removed, ability to screen for anaemia using the smartphone images slightly improves (93.1% sensitivity, 28.6% specificity).Significance.These findings provide evidence to reinforce that applying smartphone imaging techniques to understudied populations in the real world requires caution-a promising result in one group may not necessarily transfer to another demographic.

Color discrepancy of single-shade composites at different distances from the interface measured using cell phone images

Objectives

This study aimed to evaluate the impact of substrate color and interface distance on the color adjustment of 2 single-shade composites, Vittra APS Unique and Charisma Diamond One.

Materials and Methods

Dual disc-shaped specimens were created using Vittra APS Unique or Charisma Diamond One as the center composite, surrounded by shaded composites (A1 or A3). Color measurements were taken with a spectrophotometer against a gray background, recording the color coordinates in the CIELAB color space. Illumination with a light-correcting device and image acquisition using a polarizing filter-equipped cell phone were performed on specimens over the same background. Image processing software was used to measure the color coordinates in the center and periphery of the inner composite and in the outer composite. The color data were then converted to CIELAB coordinates and adjusted using data from the spectrophotometer. Color differences (ΔE00) between the center/periphery of single-shade and outer composites were calculated, along with color changes in single-shade composites caused by different outer composites. Color differences for the inner composites surrounded by A1 and A3 were also calculated. Data were analyzed using repeated-measures analysis of variance (α = 0.05).

Results

The results showed that color discrepancies were lowest near the interface and when the outer composite was whiter (A1). Additionally, Charisma Diamond One exhibited better color adjustment ability than Vittra APS Unique.

Conclusions

Color discrepancies between the investigated single-shade composites diminished towards the interface with the surrounding composite, particularly when the latter exhibited a lighter shade.

UbiNAAT: a multiplexed point-of-care nucleic acid diagnostic platform for rapid at-home pathogen detection

The COVID-19 pandemic increased demands for respiratory disease testing to facilitate treatment and limit transmission, demonstrating in the process that most existing test options were too complex and expensive to perform in point-of-care or home scenarios. Lab-based molecular techniques can detect viral RNA in respiratory illnesses but are expensive and require trained personnel, while affordable antigen-based home tests lack sensitivity for early detection in newly infected or asymptomatic individuals. The few home RNA detection tests deployed were prohibitively expensive. Here, we demonstrate a point-of-care, paper-based rapid analysis device that simultaneously detects multiple viral RNAs; it is demonstrated on two common respiratory viruses (COVID-19 and influenza A) spiked onto a commercial nasal swab. The automated device requires no sample preparation by the user after insertion of the swab, minimizing user operation steps. We incorporated lyophilized amplification reagents immobilized in a porous matrix, a novel thermally actuated valve for multiplexed fluidic control, a printed circuit board that performs on-device lysis and amplification within a cell-phone-sized disposable device. Reverse transcription loop-mediated isothermal amplification (RT-LAMP) products are visualized via fluorescent dyes using a modified cell phone, resulting in detection of as few as 104 viral copies per swab across both pathogens within 30 minutes. This integrated platform could be commercialized in a form that would be inexpensive, portable, and sensitive; it can readily be multiplexed to detect as many as 8 different RNA or DNA sequences, and adapted to any desired RNA or DNA detection assays.

Scars

Wound healing occurs as a response to disruption of the epidermis and dermis. It is an intricate and well-orchestrated response with the goal to restore skin integrity and function. However, in hundreds of millions of patients, skin wound healing results in abnormal scarring, including keloid lesions or hypertrophic scarring. Although the underlying mechanisms of hypertrophic scars and keloid lesions are not well defined, evidence suggests that the changes in the extracellular matrix are perpetuated by ongoing inflammation in susceptible individuals, resulting in a fibrotic phenotype. The lesions then become established, with ongoing deposition of excess disordered collagen. Not only can abnormal scarring be debilitating and painful, it can also cause functional impairment and profound changes in appearance, thereby substantially affecting patients' lives. Despite the vast demand on patient health and the medical society, very little progress has been made in the care of patients with abnormal scarring. To improve the outcome of pathological scarring, standardized and innovative approaches are required.

Assessment of bilirubin levels in patients with cirrhosis via forehead, sclera and lower eyelid smartphone images

One of the key biomarkers evaluating liver disease progression is an elevated bilirubin level. Here we apply smartphone imaging to non-invasive assessment of bilirubin in patients with cirrhosis. Image data was processed using two different approaches to remove variation introduced by ambient conditions and different imaging devices-a per-image calibration using a color chart in each image, and a two-step process using pairs of flash/ no-flash images to account for ambient light in combination with a one-time calibration. For the first time, results from the forehead, sclera (white of the eye) and lower eyelid were compared. The correlation coefficients between the total serum bilirubin and the predicted bilirubin via the forehead, sclera and lower eyelid were 0.79, 0.89 and 0.86 (all with p<0.001, n = 66), respectively. Given the simpler image capture for the sclera, the recommended imaging site for this patient cohort is the sclera.

Development of a thermochromic lateral flow assay to improve sensitivity for dengue virus serotype 2 NS1 detection

Dengue disease is a viral infection that has been widespread in tropical regions, such as Southeast Asia, South Asia and South America. A worldwide effort has been made over a few decades to halt the spread of the disease and reduce fatalities. Lateral flow assay (LFA), a paper-based technology, is used for dengue virus detection and identification because of its simplicity, low cost and fast response. However, the sensitivity of LFA is relatively low and is usually insufficient to meet the minimum requirement for early detection. In this study, we developed a colorimetric thermal sensing LFA format for the detection of dengue virus NS1 using recombinant dengue virus serotype 2 NS1 protein (DENV2-NS1) as a model antigen. Plasmonic gold nanoparticles, including gold nanospheres (AuNSPs) and gold nanorods (AuNRs), and magnetic nanoparticles (MNPs), namely iron oxide nanoparticles (IONPs) and zinc ferrite nanoparticles (ZFNPs), were studied for their thermal properties for sensing assays. AuNSPs with 12 nm diameter were chosen due to their great photothermal effect against light-emitting diodes (LEDs). In the thermal sensing assay, a thermochromic sheet is used as a temperature sensor transforming heat into a visible colour. In the typical LFA, the test line is visible at 6.25 ng mL-1 while our thermal sensing LFA offers a visual signal that can be observed at as low as 1.56 ng mL-1. The colorimetric thermal sensing LFA is capable of reducing the limit of detection (LOD) of DENV2-NS1 by 4 times compared to the typical visual readout. The colorimetric thermal sensing LFA can enhance the sensitivity of detection and deliver visuality to the user to translate without the need for an infrared (IR) camera. It has the potential to expand the utilities of LFA and satisfy early diagnostic applications.

A novel systems solution for accurate colorimetric measurement through smartphone-based augmented reality

Quantifying the colors of objects is useful in a wide range of applications, including medical diagnosis, agricultural monitoring, and food safety. Accurate colorimetric measurement of objects is a laborious process normally performed through a color matching test in the laboratory. A promising alternative is to use digital images for colorimetric measurement, due to their portability and ease of use. However, image-based measurements suffer from errors caused by the non-linear image formation process and unpredictable environmental lighting. Solutions to this problem often perform relative color correction among multiple images through discrete color reference boards, which may yield biased results due to the lack of continuous observation. In this paper, we propose a smartphone-based solution, that couples a designated color reference board with a novel color correction algorithm, to achieve accurate and absolute color measurements. Our color reference board contains multiple color stripes with continuous color sampling at the sides. A novel correction algorithm is proposed to utilize a first-order spatial varying regression model to perform the color correction, which leverages both the absolute color magnitude and scale to maximize the correction accuracy. The proposed algorithm is implemented as a "human-in-the-loop" smartphone application, where users are guided by an augmented reality scheme with a marker tracking module to take images at an angle that minimizes the impact of non-Lambertian reflectance. Our experimental results show that our colorimetric measurement is device independent and can reduce up to 90% color variance for images collected under different lighting conditions. In the application of reading pH values from test papers, we show that our system performs 200% better than human reading. The designed color reference board, the correction algorithm, and our augmented reality guiding approach form an integrated system as a novel solution to measure color with increased accuracy. This technique has the flexibility to improve color reading performance in systems beyond existing applications, evidenced by both qualitative and quantitative experiments on example applications such as pH-test reading.

A device-independent method for the colorimetric quantification on microfluidic sensors using a color adaptation algorithm

A general and adaptable method is proposed to reliably extract quantitative information from smartphone images of microfluidic sensors. By analyzing and processing the color information of selected standard substances, the influence of light conditions, device differences, and human factors could be significantly reduced. Machine learning and multivariate fitting methods were proved to be effective for chroma correction, and a key element was the training of sample size and the fitting form, respectively. A custom APP was developed and validated using a high-sensitivity chromium ion quantification paper chip. The average chroma deviations under different conditions were reduced by more than 75% in RGB color space, and the concentration test error was reduced by more than half compared with the commonly used method. The proposed approach could be a beneficial supplement to existing and potential colorimetry-based detection methods.

Feasibility of smartphone colorimetry of the face as an anaemia screening tool for infants and young children in Ghana

BACKGROUND

Anaemia affects approximately a quarter of the global population. When anaemia occurs during childhood, it can increase susceptibility to infectious diseases and impair cognitive development. This research uses smartphone-based colorimetry to develop a non-invasive technique for screening for anaemia in a previously understudied population of infants and young children in Ghana.

METHODS

We propose a colorimetric algorithm for screening for anaemia which uses a novel combination of three regions of interest: the lower eyelid (palpebral conjunctiva), the sclera, and the mucosal membrane adjacent to the lower lip. These regions are chosen to have minimal skin pigmentation occluding the blood chromaticity. As part of the algorithm development, different methods were compared for (1) accounting for varying ambient lighting, and (2) choosing a chromaticity metric for each region of interest. In comparison to some prior work, no specialist hardware (such as a colour reference card) is required for image acquisition.

RESULTS

Sixty-two patients under 4 years of age were recruited as a convenience clinical sample in Korle Bu Teaching Hospital, Ghana. Forty-three of these had quality images for all regions of interest. Using a naïve Bayes classifier, this method was capable of screening for anaemia (<11.0g/dL haemoglobin concentration) vs healthy blood haemoglobin concentration (≥11.0g/dL) with a sensitivity of 92.9% (95% CI 66.1% to 99.8%), a specificity of 89.7% (72.7% to 97.8%) when acting on unseen data, using only an affordable smartphone and no additional hardware.

CONCLUSION

These results add to the body of evidence suggesting that smartphone colorimetry is likely to be a useful tool for making anaemia screening more widely available. However, there remains no consensus on the optimal method for image preprocessing or feature extraction, especially across diverse patient populations.

A novel smartphone scleral-image based tool for assessing jaundice in decompensated cirrhosis patients

BACKGROUND AND AIM

Serum bilirubin is an established marker of liver disease. Reliable tools for non-invasive assessment of jaundice in cirrhosis patients, at risk of clinical decompensation, are highly desirable. While smartphone-based imaging has been described in neonatal jaundice, it has not been investigated in advanced cirrhosis patients.

METHODS

We included 46 hospitalized patients with acute cirrhosis decompensation and jaundice. Scleral images using an Android smartphone were taken to derive "Scleral Color Values (SCV)," which were matched with same day serum bilirubin measurements. In 29 patients, repeat SCV and bilirubin measurements were performed over time. We analyzed the relationship of SCV and its dynamics with serum bilirubin, clinical scores, and patient outcomes.

RESULTS

Of 46 patients, 26 (57%) had alcoholic hepatitis as the decompensation precipitant. Seven patients died during admission; a further 12 following hospital discharge. SCV had an excellent linear correlation with serum bilirubin (rho = 0.90, P < 0.001); changes in SCV and serum bilirubin across different time points, were also closely associated (rho = 0.77, P < 0.001). SCV correlated significantly with CLIF Consortium Acute Decompensation score (rho = 0.38, P < 0.001) and grade of Acute-on-Chronic Liver Failure (rho = 0.42, P = 0.039). SCV was higher in patients who died, however, not significantly (86.1 [IQR 83.0-89.7] vs 82.3 [IQR 78.5-83.3], P = 0.22). The associations of SCV with clinical parameters mirrored those of serum bilirubin.

CONCLUSION

Smartphone-based assessment of jaundice shows excellent concordance with serum bilirubin and is associated with clinical parameters in acute cirrhosis decompensation. This approach offers promise for remote assessment of cirrhosis patients at-risk of decompensation, post hospital discharge.

Secure Food-Allergen Determination by Combining Smartphone-Based Raw Image Analyses and Liquid Chromatography-Mass Spectrometry for the Quantification of Proteins Contained in Lateral Flow Assays

The current food safety testing system, based on laboratory-based quantification, is difficult to scale up in line with the growth in the export market and does not enable traceability through the nodes of the food supply system. Screening assays, for example, lateral flow assays (LFAs), can improve traceability but often lack the required reliability to guarantee compliance. Here, we present an alternative pipeline for secure on-site compliance testing, using allergens as a case study. The pipeline features smartphone-driven LFA quantification and an liquid chromatography-mass spectrometry (LC-MS) method enabling direct quantification of the allergens contained in the LFA. The system enables swift and objective screening and provides a control measure to verify LFA assay reliability. For the smartphone assay, 8-bit RGB and grayscale colorimetric channels were compared with 16-bit raw intensity values. The latter outperformed RGB and grayscale channels in sensitivity, repeatability, and precision, while ratiometric ambient light correction resulted in excellent robustness for light-intensity variation. Calibration curves for peanut determination using two commercial LFAs featured excellent analytical parameters (R² = 0.97-0.99; RSD 7-1%; LOD 3-7 ppm). Gluten determination with a third commercial LFA was equally established. A prediction error of 13 ± 11% was achieved for the best performing assay. Good performance-calibration curves (R² = 0.93-0.99) and CVs (<15%)- were observed for the analyte quantification from the LFA by LC-MS. The LOD for the LC-MS assay was 0.5 ppm, well below the LODs reported for the LFAs. This method creates a digital, fast, and secure food safety compliance testing paradigm that can benefit the industry and consumer alike.

Validating a Sclera-Based Smartphone Application for Screening Jaundiced Newborns in Ghana

OBJECTIVES

Reducing the burden of bilirubin-induced neurologic complications in low-resource countries requires reliable and accessible screening tools. We sought to optimize and validate a sclera-based smartphone application, Neonatal Scleral-Conjunctival Bilirubin (neoSCB), for screening neonatal jaundice.

METHODS

Using a cross-sectional design, consecutive eligible infants (aged 0-28 days, in the hospital, not critically ill) were enrolled in Ghana from March 2019 to April 2020. Jaundice screening was performed with neoSCB (Samsung Galaxy S8) to quantify SCB and JM-105 (Dräger) for transcutaneous bilirubin (TcB). Screening values were compared with total serum bilirubin (TSB) measured at the point of care.

RESULTS

Overall, 724 infants participated in the optimization and validation phases of the study. The analysis for validation included 336 infants with no previous treatment of jaundice. Single neoSCB image captures identified infants with TSB >14.62 mg/dL (250 μmol/L) with reasonably high sensitivity, specificity, and receiver operating characteristic area under the curve at 0.94 (95% confidence interval [CI], 0.91 to 0.97), 0.73 (95% CI, 0.68 to 0.78), and 0.90, respectively. These findings were comparable to the sensitivity and specificity of JM-105 (0.96 [95% CI, 0.90 to 0.99] and 0.81 [95% CI, 0.76 to 0.86], respectively). The TcB/TSB had a larger correlation coefficient (r = 0.93; P < .01) than SCB/TSB (r = 0.78; P < .01). Performance of both devices was lower in infants with previous phototherapy (n = 231).

CONCLUSIONS

The diagnostic performance of neoSCB was comparable to JM-105 and is a potential, affordable, contact-free screening tool for neonatal jaundice.

Smartphones’ Skin Colour Reproduction Analysis for Neonatal Jaundice Detection

Abstract In recent years, smartphone-based colour imaging systems are being increasingly used for Neonatal jaundice detection applications. These systems are based on the estimation of bilirubin concentration levels that correlates with newborns’ skin colour images corresponding to total serum bilirubin (TSB) and transcutaneous bilirubinometry (TcB) measurements. However, the colour reproduction capacity of smartphone cameras are known to be influenced by various factors including the technological and acquisition process variabilities. To make an accurate bilirubin estimation, irrespective of the type of smartphone and illumination conditions used to capture the newborns’ skin images, an inclusive and complete model, or data set, which can represent all the possible real world acquisitions scenarios needs to be utilized. Due to various challenges in generating such a model or a data set, some solutions tend towards the application of reduced data set (designed for reference conditions and devices only) and colour correction systems (for the transformation of other smartphone skin images to the reference space). Such approaches will make the bilirubin estimation methods highly dependent on the accuracy of their employed colour correction systems, and the capability of reducing device-to-device colour reproduction variability. However, the state-of-the-art methods with similar methodologies were only evaluated and validated on a single smartphone camera. The vulnerability of the systems in making an incorrect jaundice diagnosis can only be shown with a thorough investigation of the colour reproduction variability for extended number of smartphones and illumination conditions. Accordingly, this work presents and discuss the results of such broad investigation, including the evaluation of seven smartphone cameras, ten light sources, and three different colour correction approaches. The overall results show statistically significant colour differences among devices, even after colour correction applications, and that further analysis on clinically significance of such differences is required for skin colour based jaundice diagnosis.

Smartphone digital image colorimetric determination of the total monomeric anthocyanin content in black rice via the pH differential method

In this research, the pH differential method was explored for the first time using a mobile phone as a detector, replacing UV-Vis spectrophotometry. A smartphone digital image colorimetric (SDIC) system was developed for the determination of the total monomeric anthocyanin content in black rice grains using colour values. The change in colour of anthocyanin cyanidin-3-glucoside (C3G) at pH 1.0 and pH 4.5 was investigated and described through colour model systems (RGB and CIELAB). Under optimum conditions, the quantitative method based on the chroma difference, was able to quantify the total amount of monomeric anthocyanins with a linear correlation (R² = 0.989) to that of UV-Vis spectrophotometry and high performance liquid chromatography (HPLC) (reference method). The SDIC system displayed good precision (≤1.88% RSD) and a low detection limit (2.2 ± 0.1 μg g^-1). The validated results demonstrated that the developed method was a cost-effective alternative for the quantitation of anthocyanins. In addition, the effect of six mineral elements on black rice cultivation was investigated. The results showed that the addition of the Ca fertiliser resulted in black rice grains with an anthocyanin content 2-fold higher than that of the control with a significant difference (p < 0.05).

Dual colorimetric strategy for specific DNA detection by nicking endonuclease-assisted gold nanoparticle signal amplification

The continuous spread of invasive alien species, as zebra mussel (Dreissena polymorpha), is a major global concern and it is urgent to stop it. Early stages of an invasion are crucial and challenging; however, detection tools based on environmental DNA analysis are promising alternatives. We present an alternative DNA target amplification strategy for signal enhancement followed by dual-mode colorimetric naked eye and optical smartphone analysis for the early detection of zebra mussel environmental DNA. Target amplification was designed based on the nicking endonuclease probe cleavage upon probe and complementary target hybridization. The cleaved/intact probe interacts with DNA-modified nanoparticles for colorimetric detection. We have demonstrated that enzyme amplification strategy enhanced 12-fold the sensitivity by naked eye detection, achieving a detection limit of ~8 nM (4.48×10¹⁰ copies) in controlled conditions, whereas target in complex environmental samples allowed the detection of 22.5 nM (1.26×10¹¹ copies). Competitive assays also showed that the system can discriminate specific zebra mussel DNA sequences from other DNA sequences. Additionally, smartphone analysis for DNA quantification further improved the sensitivity of its detection by 130-fold, more than 2 orders of magnitude, when applied to environmental samples. The limit of detection to 0.17 nM (9.52×10⁸ copies) is based on RGB coordinates, which is especially relevant to monitor early aggregation stages, being more accurate and reducing naked eye detection subjectivity. DNA extracted from zebra mussel meat, zebra mussel contaminated river water, and non-contaminated river water samples were successfully tested. Dual-mode colorimetric detection is useful in field analysis without the need for expensive laboratory equipment.

Smartphone-based imaging systems for medical applications: a critical review

SIGNIFICANCE

Smartphones come with an enormous array of functionality and are being more widely utilized with specialized attachments in a range of healthcare applications. A review of key developments and uses, with an assessment of strengths/limitations in various clinical workflows, was completed.

AIM

Our review studies how smartphone-based imaging (SBI) systems are designed and tested for specialized applications in medicine and healthcare. An evaluation of current research studies is used to provide guidelines for improving the impact of these research advances.

APPROACH

First, the established and emerging smartphone capabilities that can be leveraged for biomedical imaging are detailed. Then, methods and materials for fabrication of optical, mechanical, and electrical interface components are summarized. Recent systems were categorized into four groups based on their intended application and clinical workflow: ex vivo diagnostic, in vivo diagnostic, monitoring, and treatment guidance. Lastly, strengths and limitations of current SBI systems within these various applications are discussed.

RESULTS

The native smartphone capabilities for biomedical imaging applications include cameras, touchscreens, networking, computation, 3D sensing, audio, and motion, in addition to commercial wearable peripheral devices. Through user-centered design of custom hardware and software interfaces, these capabilities have the potential to enable portable, easy-to-use, point-of-care biomedical imaging systems. However, due to barriers in programming of custom software and on-board image analysis pipelines, many research prototypes fail to achieve a prospective clinical evaluation as intended. Effective clinical use cases appear to be those in which handheld, noninvasive image guidance is needed and accommodated by the clinical workflow. Handheld systems for in vivo, multispectral, and quantitative fluorescence imaging are a promising development for diagnostic and treatment guidance applications.

CONCLUSIONS

A holistic assessment of SBI systems must include interpretation of their value for intended clinical settings and how their implementations enable better workflow. A set of six guidelines are proposed to evaluate appropriateness of smartphone utilization in terms of clinical context, completeness, compactness, connectivity, cost, and claims. Ongoing work should prioritize realistic clinical assessments with quantitative and qualitative comparison to non-smartphone systems to clearly demonstrate the value of smartphone-based systems. Improved hardware design to accommodate the rapidly changing smartphone ecosystem, creation of open-source image acquisition and analysis pipelines, and adoption of robust calibration techniques to address phone-to-phone variability are three high priority areas to move SBI research forward.