Smartphone-based optical spectroscopic platforms for biomedical applications: a review [Invited]

Smartphone conjunctiva photography for malaria risk stratification in asymptomatic school age children

Malaria remains a major global health challenge. Although effective control relies on testing all suspected cases, asymptomatic infections in school-age children are frequently overlooked. Advances in retinal imaging and computer vision have enhanced malaria detection. However, noninvasive, point-of-care malaria detection remains unrealized, partly because of the need for specialized equipment. Here we report radiomic analyses of 4302 photographs of the palpebral conjunctiva captured using unmodified smartphone cameras from asymptomatic 405 participants aged 5 to 15 years to predict malaria risk. Our neural network classification model of radiomic features achieves an area under the receiver operating characteristic curve of 0.76 with 95% confidence intervals from 0.68 to 0.84 in distinguishing between malaria-infected and non-infected cases in endemic regions. Photographing the inner eyelid provides the advantages of easy accessibility and direct exposure to the microvasculature. This mobile health approach has the potential for malaria prescreening and managing febrile illness in resource-limited settings.

Smartphones as a platform for molecular analysis: concepts, methods, devices and future potential

Over the past 15 years, smartphones have had a transformative effect on everyday life. These devices also have the potential to transform molecular analysis over the next 15 years. The cameras of a smartphone, and its many additional onboard features, support optical detection and other aspects of engineering an analytical device. This article reviews the development of smartphones as platforms for portable chemical and biological analysis. It is equal parts conceptual overview, technical tutorial, critical summary of the state of the art, and outlook on how to advance smartphones as a tool for analysis. It further discusses the motivations for adopting smartphones as a portable platform, summarizes their enabling features and relevant optical detection methods, then highlights complementary technologies and materials such as 3D printing, microfluidics, optoelectronics, microelectronics, and nanoparticles. The broad scope of research and key advances from the past 7 years are reviewed as a prelude to a perspective on the challenges and opportunities for translating smartphone-based lab-on-a-chip devices from prototypes to authentic applications in health, food and water safety, environmental monitoring, and beyond. The convergence of smartphones with smart assays and smart apps powered by machine learning and artificial intelligence holds immense promise for realizing a future for molecular analysis that is powerful, versatile, democratized, and no longer just the stuff of science fiction.

Green Microextraction, Paper-Based Technique, and Smartphone Sensing for Sustainable Determination of Nicotinamide in Pharmaceuticals and Blood Samples

This study presents the development of two simple, sensitive, and selective microextraction and preconcentration procedures for determining nicotinamide (NAM) in pharmaceutical formulations and blood samples. The methods utilize the König reaction, where cyanogen chloride, formed by reacting potassium thiocyanate with sodium hypochlorite in an acidic medium, interacts with NAM and couples with buffered barbituric acid at pH 3.5 to form a pink polymethine dye. This dye is extracted into an isobutanol layer using tetrabutylammonium bromide and exhibits maximum absorption at 560 nm for spectrophotometric quantification. In the smartphone paper-based (SPB) method, the dye is applied to a paper strip, captured by a smartphone, and analyzed for red, green, and blue components. Both methods were thoroughly evaluated for key parameters, demonstrating adherence to Beer's law over a NAM concentration range of 1.0-7.8 µg/mL, with limits of detection of 0.76 µg/mL for the spectrophotometric method and 0.91 µg/mL for the SPB method. Our SPB combines paper-based analysis, smartphone detection, and microextraction for the first time, offering a cost-effective, portable, and sensitive solution for NAM assay in plasma. A comparison with the established high-performance liquid chromatography method, using statistical tests, showed no significant differences, confirming the reliability of these novel methods.

Visible diffuse reflectance smartphone spectrometer with high spectral accuracy

A smartphone-based spectrometer employing principle of diffuse reflection is reported for the surface analysis of solid samples. The instrument utilizes a thin-film grating to diffract incoming light, while a diffuse reflecting surface projects the image of this diffracted light onto the detector plane. The CMOS camera of smartphone camera directly captures the diffusely reflected photons within its limited field-of-view thus eliminating the need for collection, conditioning and converging optics. The optical setup of the instrument provides facility to calibrate the spectral response considering the nonlinear distribution of the wavelength across the diffraction direction. Additional correction in the detector response at different light intensity results a reduced spectral error with a maximum wavelength resolution of δλ=0.08 nm/pixel in the camera within the spectral range Δλ = (400 - 700) nm. As a proof of the concept, the instrument demonstrates successful detection of color pigments in food samples by absorption measurement of the samples at an average spectral error < 6 %. The distinct absorption peak associated with standard food colors are compared against the absorption profile of unknown food colors used in pastry cake. This field-functional smart analysis with internet connectivity opens opportunity of identifying food adulteration by using toxic chemical colors at the point-of-test and immediate reporting to others. The overall instrument is fabricated by utilizing low-cost and light weight plastic wood to make compact (110 mm × 105 mm × 125 mm), robust, inexpensive (∼$ 50) and suitable for field-portable (∼145 gm) hand-held operation.

Towards ultra-low-cost smartphone microscopy

The outbreak of COVID-19 exposed the inadequacy of our technical tools for home health surveillance, and recent studies have shown the potential of smartphones as a universal optical microscopic imaging platform for such applications. However, most of them use laboratory-grade optomechanical components and transmitted illuminations to ensure focus tuning capability and imaging quality, which keeps the cost of the equipment high. Here, we propose an ultra-low-cost solution for smartphone microscopy. To realize focus tunability, we designed a seesaw-like structure capable of converting large displacements on one side into small displacements on the other (reduced to ∼9.1%), which leverages the intrinsic flexibility of 3D printing materials. We achieved a focus-tuning accuracy of ∼5 𝜇m, which is 40 times higher than the machining accuracy of the 3D-printed lens holder itself. For microscopic imaging, we used an off-the-shelf smartphone camera lens as the objective and the built-in flashlight as the illumination. To compensate for the resulting image quality degradation, we developed a learning-based image enhancement method. We used the CycleGAN architecture to establish the mapping from smartphone microscope images to benchtop microscope images without pairing. We verified the imaging performance on different biomedical samples. Except for the smartphone, we kept the full costs of the device under 4 USD. We think these efforts to lower the costs of smartphone microscopes will benefit their applications in various scenarios, such as point-of-care testing, on-site diagnosis, and home health surveillance. RESEARCH HIGHLIGHTS: We propose a solution for ultra-low-cost smartphone microscopy. Utilizing the flexibility of 3D-printed material, we can achieve focusing accuracy of ∼5 𝜇m. Such a low-cost device will benefit point-of-care diagnosis and home health surveillance.

Design of a handheld and portable fluorescence imaging system for quantitative detection of pregnancy-specific biomarkers in cattle

Reproductive management significantly impacts dairy farm productivity, necessitating accurate timely pregnancy detection in cattle. This paper presents a novel handheld and portable fluorescence imaging system designed for quantitative assessment of pregnancy-specific biomarkers, addressing the limitations of current detection methods. The objective was to develop a cost-effective, at-farm solution for detecting pregnancy-specific protein B (PSPB) in bovine plasma samples. The system integrates an imaging module and a custom software application, enabling image capture, data processing, and PSPB concentration determination. Calibration utilizing known PSPB concentrations achieved a 0.6 ng/mL limit of detection. Validation encompassed a comparison with a standard ELISA method using 100 bovine plasma samples; minimal bias and good agreement were observed within the linear range of the calibration curve for both methods. The system offers portability, user-friendliness, and potential for multiplex detection, promising real-time, at-farm reproductive management. This study demonstrates the successful development and validation of a portable fluorescence imaging system, offering an efficient and accurate approach to detecting pregnancy-specific biomarkers in cattle. Its implications extend to improving dairy farm productivity by enabling timely and reliable reproductive management practices.

Rapid smartphone-based assays for pesticides inspection in foods: current status, limitations, and future directions

Smartphone-based assays to inspect pesticides in foods have attracted much attention as such assays can transform tedious laboratory-based assays into real-time, on-site, or even home-based assay and hence overcoming the limitations of conventional assays. Although an array of smartphone-based assays is available, information on the use of these assays for pesticides inspection is scattered. The purposes of this review are therefore to compile, summarize and discuss state-of-the-art as well as advantages and limitations of the relevant technologies. Suggestions are provided for further development of smartphone-based assays for rapid inspection of pesticides in foods. Smartphone-based assays relying on enzyme inhibitions are noted to be nonselective qualitative, capable of reporting results in a quantitative manner only when a sample contains an individual pesticide. Smartphone-based assays relying on chemical reactions also target only individual pesticides. Smartphone-based visible spectroscopy can, on the other hand, inspect individual and multiple pesticides with the aid of appropriate colorimetry-, luminescence-, or fluorescence-based assay. Smartphone-based visible-near infrared and Raman spectroscopies are suitable for simultaneous multiple pesticides inspection. Raman spectroscopy is of particular interest as it can detect pesticides even at lower concentrations. This spectroscopic technique can also serve as a real-time assay with the aid of cloud network computations.

Portable optical fiber biosensors integrated with smartphone: technologies, applications, and challenges [Invited]

The increasing demand for individualized health monitoring and diagnostics has prompted considerable research into the integration of portable optical fiber biosensors integrated with smartphones. By capitalizing on the benefits offered by optical fibers, these biosensors enable qualitative and quantitative biosensing across a wide range of applications. The integration of these sensors with smartphones, which possess advanced computational power and versatile sensing capabilities, addresses the increasing need for portable and rapid sensing solutions. This extensive evaluation thoroughly examines the domain of optical fiber biosensors in conjunction with smartphones, including hardware complexities, sensing approaches, and integration methods. Additionally, it explores a wide range of applications, including physiological and chemical biosensing. Furthermore, the review provides an analysis of the challenges that have been identified in this rapidly evolving area of research and concludes with relevant suggestions for the progression of the field.

On-site quantitation of xanthine in fish and serum using a smartphone-based spectrophotometer integrated with a dual-readout nanosensing assay

Rapid and quantitative biochemical analysis at points-of-need is imperative for food safety inspection. This work reports on: 1) a stand-alone smartphone-based "two-in-one" spectrophotometer (the SAFS) installed with a self-developed application (the SAFS-App) which can precisely collect both absorption spectra and fluorescence spectra in a reproducible manner within 5 s; and 2) a straightforward protocol for xanthine detection using fluorescent carbon nanodots and silver nanoparticles. The assay performed with the SAFS demonstrates high specificity towards xanthine, and a linear range of 1-60 μM with LODs of 0.38 and 0.58 μM for colorimetric and fluorometric readouts, respectively. The reliability and robustness of the SAFS are validated by on-site quantitation of xanthine in fish and serum samples, with comparable accuracy to HPLC method. More importantly, the SAFS presents itself as an appealing device which is accessible to everyone through the Internet of Things and can be tailored for diverse point-of-care testing applications.

Diffuse transmittance visible spectroscopy using smartphone flashlight for photoplethysmography and vital signs measurements

Photoplethysmography (PPG), with its wide range of applications, has become one of the most promising modalities for healthcare monitoring technology. In this work, we present a new PPG measurement technique based on diffuse transmittance spectroscopy (DTS) with the help of a smartphone built-in flashlight as an alternative broadband light source. The blood Volume Pulse (BVP) signal was extracted from recorded transmittance spectra at 620 nm. The results were compared with the ground truth and conventional contact finger PPG sensors. A very high correlation was found between the diffuse transmittance signal and the reference PPG signals (r = 0.997, p < 0.0001). The accuracy and root mean square error (RMSE) were 99.23% and 0.8 bpm, respectively. In addition, a Bland-Altman analysis showed a good agreement between both techniques, with a very small bias between mean paired differences of heart rate observations. A simple forward model for diffuse transmittance spectra for different levels of blood oxygen saturation is developed and supported by experimental measurements. It was also found that blood oxygen saturation (SpO2) can be estimated with the aid of DTS based smartphone flash by tracking the wavelength corresponding to the oxygenation level in the visible range between orange and red regions of the visible spectrum particularly in the range between 610 and 635 nm for 26 healthy subjects. 624 nm on average seems to be the wavelength that corresponds with the normal blood oxygenation level. These findings show the potential of DTS PPG to reliably extract cardiac frequency and estimate SpO2 with adequate accuracy. The results also demonstrate the capability of smartphone flash as a miniature visible light source for recording multispectral PPG signals and quantifying vital signs in the transmission mode at the fingertip with acceptable signal quality over a wide range of wavelengths from 550 nm to 650 nm.

Exploring the Clinical Utility of Raman Spectroscopy for Point-of-Care Cardiovascular Disease Biomarker Detection

A variety of innovative point-of-care (POC) solutions using Raman systems have been explored. However, the vast effort is in assay development, while studies of the characteristics required for Raman spectrometers to function in POC applications are lacking. In this study, we tested and compared the performance of eight commercial Raman spectrometers ranging in size from benchtop Raman microscopes to portable and handheld Raman spectrometers using paper fluidic cartridges, including their ability to detect cardiac troponin I and heart fatty acid binding protein, both of which are well-established biomarkers for evaluating cardiovascular health. Each spectrometer was evaluated in terms of excitation wavelength, laser characteristics, and ease of use to investigate POC utility. We found that the Raman spectrometers equipped with 780 and 785 nm laser sources exhibited a reduced background signal and provided higher sensitivity compared to those with 633 and 638 nm laser sources. Furthermore, the spectrometer equipped with the single acquisition line readout functionality showed improved performance when compared to the point scan spectrometers and allowed measurements to be made faster and easier. The portable and handheld spectrometers also showed similar detection sensitivity to the gold standard instrument. Lastly, we reduced the laser power for the spectrometer with single acquisition line readout capability to explore the system performance at a laser power that change the classification from a Class 3B laser device to a Class 3R device and found that it showed comparable performance. Overall, these findings show that portable Raman spectrometers have the potential to be used in POC settings with accuracy comparable to laboratory-grade instruments, are relatively low-cost, provide fast signal readout, are easy to use, and can facilitate access for underserved communities.

SmartOCT: smartphone-integrated optical coherence tomography

Smartphone devices have seen unprecedented technical innovation in computational power and optical imaging capabilities, making them potentially invaluable tools in scientific imaging applications. The smartphone's compact form-factor and broad accessibility has motivated researchers to develop smartphone-integrated imaging systems for a wide array of applications. Optical coherence tomography (OCT) is one such technique that could benefit from smartphone-integration. Here, we demonstrate smartOCT, a smartphone-integrated OCT system that leverages built-in components of a smartphone for detection, processing and display of OCT data. SmartOCT uses a broadband visible-light source and line-field OCT design that enables snapshot 2D cross-sectional imaging. Furthermore, we describe methods for processing smartphone data acquired in a RAW data format for scientific applications that improves the quality of OCT images. The results presented here demonstrate the potential of smartphone-integrated OCT systems for low-resource environments.

Continuous roller nanoimprinting: next generation lithography

Nanoimprint lithography (NIL) is a cost-effective and high-throughput technique for replicating nanoscale structures that does not require expensive light sources for advanced photolithography equipment. NIL overcomes the limitations of light diffraction or beam scattering in traditional photolithography and is suitable for replicating nanoscale structures with high resolution. Roller nanoimprint lithography (R-NIL) is the most common NIL technique benefiting large-scale, continuous, and efficient industrial production. In the past two decades, a range of R-NIL equipment has emerged to meet the industrial needs for applications including biomedical devices, semiconductors, flexible electronics, optical films, and interface functional materials. R-NIL equipment has a simple and compact design, which allows multiple units to be clustered together for increased productivity. These units include transmission control, resist coating, resist curing, and imprinting. This critical review summarizes the hitherto R-NIL processes, their typical technical problems, and corresponding solutions and gives guidelines for developing advanced R-NIL equipment.

mHealth hyperspectral learning for instantaneous spatiospectral imaging of hemodynamics

Hyperspectral imaging acquires data in both the spatial and frequency domains to offer abundant physical or biological information. However, conventional hyperspectral imaging has intrinsic limitations of bulky instruments, slow data acquisition rate, and spatiospectral trade-off. Here we introduce hyperspectral learning for snapshot hyperspectral imaging in which sampled hyperspectral data in a small subarea are incorporated into a learning algorithm to recover the hypercube. Hyperspectral learning exploits the idea that a photograph is more than merely a picture and contains detailed spectral information. A small sampling of hyperspectral data enables spectrally informed learning to recover a hypercube from a red-green-blue (RGB) image without complete hyperspectral measurements. Hyperspectral learning is capable of recovering full spectroscopic resolution in the hypercube, comparable to high spectral resolutions of scientific spectrometers. Hyperspectral learning also enables ultrafast dynamic imaging, leveraging ultraslow video recording in an off-the-shelf smartphone, given that a video comprises a time series of multiple RGB images. To demonstrate its versatility, an experimental model of vascular development is used to extract hemodynamic parameters via statistical and deep learning approaches. Subsequently, the hemodynamics of peripheral microcirculation is assessed at an ultrafast temporal resolution up to a millisecond, using a conventional smartphone camera. This spectrally informed learning method is analogous to compressed sensing; however, it further allows for reliable hypercube recovery and key feature extractions with a transparent learning algorithm. This learning-powered snapshot hyperspectral imaging method yields high spectral and temporal resolutions and eliminates the spatiospectral trade-off, offering simple hardware requirements and potential applications of various machine learning techniques.

Advances on microfluidic paper-based electroanalytical devices

Since the inception of the first electrochemical devices on paper substrates, many different reports of microfluidic paper-based electroanalytical devices (μPEDs), innovative hydrophobic barriers and electrode fabrication processes have allowed the incorporation of diverse materials, resulting in different applications and a boost in performance. These advancements have led to the creation of paper-based devices with comparable performance to many standard conventional devices, with the added benefits of pumpless fluidic transport, component separation and reagent storage that can be exploited to automate and handle sample preprocessing. Herein, we review μPEDs, summarize the characteristics and functionalities of μPEDs, such as separation, fluid flow control and storage, and outline the conventional and emerging fabrication and modification approaches for μPEDs. We also examine the recent application of μPEDs in biomedicine, the environment, and food and water safety, as well as some limitations and challenges that must be addressed.

Conventional methods and future trends in antimicrobial susceptibility testing

Antimicrobial susceptibility testing is an essential task for selecting appropriate antimicrobial agents to treat infectious diseases. Constant evolution has been observed in methods used in the diagnostic microbiology laboratories. Disc diffusion or broth microdilution are classical and conventional phenotypic methods with long turnaround time and labour-intensive but still widely practiced as gold-standard. Scientists are striving to develop innovative, novel and faster methods of antimicrobial susceptibility testing to be applicable for routine microbiological laboratory practice and research. To meet the requirements, there is an increasing trend towards automation, genotypic and micro/nano technology-based innovations. Automation in detection systems and integration of computers for online data analysis and data sharing are giant leaps towards versatile nature of automated methods currently in use. Genotypic methods detect a specific genetic marker associated with resistant phenotypes using molecular amplification techniques and genome sequencing. Microfluidics and microdroplets are recent addition in the continuous advancement of methods that show great promises with regards to safety and speed and have the prospect to identify and monitor resistance mechanisms. Although genotypic and microfluidics methods have many exciting features, however, their applications into routine clinical laboratory practice warrant extensive validation. The main impetus behind the evolution of methods in antimicrobial susceptibility testing is to shorten the overall turnaround time in obtaining the results and to enhance the ease of sample processing. This comprehensive narrative review summarises major conventional phenotypic methods and automated systems currently in use, and highlights principles of some of the emerging genotypic and micro/nanotechnology-based methods in antimicrobial susceptibility testing.

Smartphone-read phage lateral flow assay for point-of-care detection of infection

The COVID-19 pandemic has highlighted the urgent need for sensitive, affordable, and widely accessible testing at the point of care. Here we demonstrate a new, universal LFA platform technology using M13 phage conjugated with antibodies and HRP enzymes that offers high analytical sensitivity and excellent performance in a complex clinical matrix. We also report its complete integration into a sensitive chemiluminescence-based smartphone-readable lateral flow assay for the detection of SARS-CoV-2 nucleoprotein. We screened 84 anti-nucleoprotein monoclonal antibody pairs in phage LFA and identified an antibody pair that gave an LoD of 25 pg mL-1 nucleoprotein in nasal swab extract using a FluorChem gel documentation system and 100 pg mL-1 when the test was imaged and analyzed by an in-house-developed smartphone reader. The smartphone-read LFA signals for positive clinical samples tested (N = 15, with known Ct) were statistically different (p < 0.001) from signals for negative clinical samples (N = 11). The phage LFA technology combined with smartphone chemiluminescence imaging can enable the timely development of ultrasensitive, affordable point-of-care testing platforms for SARS-CoV-2 and beyond.

Computational Portable Microscopes for Point-of-Care-Test and Tele-Diagnosis

In bio-medical mobile workstations, e.g., the prevention of epidemic viruses/bacteria, outdoor field medical treatment and bio-chemical pollution monitoring, the conventional bench-top microscopic imaging equipment is limited. The comprehensive multi-mode (bright/dark field imaging, fluorescence excitation imaging, polarized light imaging, and differential interference microscopy imaging, etc.) biomedical microscopy imaging systems are generally large in size and expensive. They also require professional operation, which means high labor-cost, money-cost and time-cost. These characteristics prevent them from being applied in bio-medical mobile workstations. The bio-medical mobile workstations need microscopy systems which are inexpensive and able to handle fast, timely and large-scale deployment. The development of lightweight, low-cost and portable microscopic imaging devices can meet these demands. Presently, for the increasing needs of point-of-care-test and tele-diagnosis, high-performance computational portable microscopes are widely developed. Bluetooth modules, WLAN modules and 3G/4G/5G modules generally feature very small sizes and low prices. And industrial imaging lens, microscopy objective lens, and CMOS/CCD photoelectric image sensors are also available in small sizes and at low prices. Here we review and discuss these typical computational, portable and low-cost microscopes by refined specifications and schematics, from the aspect of optics, electronic, algorithms principle and typical bio-medical applications.

An improved spectral estimation method based on color perception features of mobile phone camera

We use the mobile phone camera as a new spectral imaging device to obtain raw responses of samples for spectral estimation and propose an improved sequential adaptive weighted spectral estimation method. First, we verify the linearity of the raw response of the cell phone camera and investigate its feasibility for spectral estimation experiments. Then, we propose a sequential adaptive spectral estimation method based on the CIE1976 L*a*b* (CIELAB) uniform color space color perception feature. The first stage of the method is to weight the training samples and perform the first spectral reflectance estimation by considering the Lab color space color perception features differences between samples, and the second stage is to adaptively select the locally optimal training samples and weight them by the first estimated root mean square error (RMSE), and perform the second spectral reconstruction. The novelty of the method is to weight the samples by using the sample in CIELAB uniform color space perception features to more accurately characterize the color difference. By comparing with several existing methods, the results show that the method has the best performance in both spectral error and chromaticity error. Finally, we apply this weighting strategy based on the CIELAB color space color perception feature to the existing method, and the spectral estimation performance is greatly improved compared with that before the application, which proves the effectiveness of this weighting method.

Bimodal polarization-sensitive imaging and diffuse reflectance spectroscopy facilitated rapid augmented reality for tissue stratification

We reported the development of a bimodal large field of view (~95 cm² ) polarization-sensitive (PS) imaging and point-wise diffuse reflectance (DR) spectroscopy platform synergising the advantages of the two modalities. PS-DR spectroscopy allows simultaneous label-free biochemical and structural analysis of the investigated tissue. For real applications, the PS imaging first grossly stratified tissue into different categories, followed by high information dimension PS-DR spectroscopy ascertaining ambiguous tissue regions identified by the PS imaging. Tested on a tissue phantom consisting of porcine esophagus muscularis propria and submucosa, it has demonstrated the system developed could complete tissue interrogation within 0.6 minutes and with separation accuracy of 95.87%. Further test on tissue phantom consisting of natural and crushed bovine tendon mimicking normal and cancerous breast tissues validated the potential of system developed to effectively and rapidly investigate large tissue area, facilitating augmented tissue boundary demarcation.

Design, fabrication and testing of 3D printed smartphone-based device for collection of intrinsic fluorescence from human cervix

Fluorescence spectroscopy has the potential to identify discriminatory signatures, crucial for early diagnosis of cervical cancer. We demonstrate here the design, fabrication and testing of a 3D printed smartphone based spectroscopic device. Polarized fluorescence and elastic scattering spectra are captured through the device using a 405 nm laser and a white LED source respectively. The device has been calibrated by comparison of spectra of standard fluorophores (Flavin adenine dinucleotide, fluorescein, rhodamine, and porphyrin) with the corresponding spectra collected from a commercial spectrometer. A few cervical tissue spectra have also been captured for proof of its applicability as a portable, standalone device for the collection of intrinsic fluorescence spectra from human cervix.

Improved method for spectral reflectance estimation and application to mobile phone cameras

We propose an improved method for estimating surface-spectral reflectance from the image data acquired by an RGB digital camera. We suppose a multispectral image acquisition system in the visible range, where a camera captures multiple images for the scene of an object under multiple light sources. First, the observed image data are described using the camera spectral sensitivities, the surface-spectral reflectance, the illuminant spectral power distributions, an additive noise term, and a gain parameter. Then, the optimal reflectance estimate is determined to minimize the mean-square error between the estimate and the original surface-spectral reflectance. We attempt to further improve the estimation accuracy and develop a novel linear estimator in a more general form than the Wiener estimator. Furthermore, we calibrate the imaging system using a reference standard sample. Finally, experiments are performed to validate the proposed method for estimating the surface-spectral reflectance using different mobile phone cameras.

Optical imaging spectroscopy for rapid, primary screening of SARS-CoV-2: a proof of concept

Effective testing is essential to control the coronavirus disease 2019 (COVID-19) transmission. Here we report a-proof-of-concept study on hyperspectral image analysis in the visible and near-infrared range for primary screening at the point-of-care of SARS-CoV-2. We apply spectral feature descriptors, partial least square-discriminant analysis, and artificial intelligence to extract information from optical diffuse reflectance measurements from 5 µL fluid samples at pixel, droplet, and patient levels. We discern preparations of engineered lentiviral particles pseudotyped with the spike protein of the SARS-CoV-2 from those with the G protein of the vesicular stomatitis virus in saline solution and artificial saliva. We report a quantitative analysis of 72 samples of nasopharyngeal exudate in a range of SARS-CoV-2 viral loads, and a descriptive study of another 32 fresh human saliva samples. Sensitivity for classification of exudates was 100% with peak specificity of 87.5% for discernment from PCR-negative but symptomatic cases. Proposed technology is reagent-free, fast, and scalable, and could substantially reduce the number of molecular tests currently required for COVID-19 mass screening strategies even in resource-limited settings.

Smartphone-Based Refractive Index Optosensing Platform Using a DVD Grating

A low-cost, smartphone-based optical diffraction grating refractometer is demonstrated. Its principle of operation is based on the dependence of the diffraction efficiency of a DVD grating on the surrounding refractive index. The studied configuration uses the built-in LED flashlight and camera of a smartphone as a light source and a detector, respectively, to image the DVD grating diffraction pattern. No additional optical accessories, such as lenses, fibers, filters, or pinholes, are employed. The refractive index sensor exhibits a linear response in the refractive index range of 1.333–1.358 RIU (refractive index unit), with a sensitivity of 32.4 RIU⁻¹ and a resolution of 2 × 10⁻³ RIU at the refractive index of water. This performance makes the proposed scheme suitable for affinity-based biosensing and a promising optosensing refractometric platform for point-of-need applications.

A multi-channel smartphone-based spectroscopic system for high-throughput biosensing in low-resource settings

Simultaneous detection of multiple samples can improve the effectiveness of the point-of-care strategies. We have demonstrated a novel optical system that allows detection of multiple analytes at the same time using a smartphone spectrometer.

Ultracompact fluorescence smartphone attachment using built-in optics for protoporphyrin-IX quantification in skin

Smartphone-based fluorescence imaging systems have the potential to provide convenient quantitative image guidance at the point of care. However, common approaches have required the addition of complex optical attachments, which reduce translation potential. In this study, a simple clip-on attachment appropriate for fluorescence imaging of protoporphyrin-IX (PpIX) in skin was designed using the built-in light source and ultrawide camera sensor of a smartphone. Software control for image acquisition and quantitative analysis was developed using the 10-bit video capability of the phone. Optical performance was characterized using PpIX in liquid tissue phantoms and endogenously produced PpIX in mice and human skin. The proposed system achieves a very compact form factor (<30 cm3) and can be readily fabricated using widely available low-cost materials. The limit of detection of PpIX in optical phantoms was <10 nM, with good signal linearity from 10 to 1000 nM (R2 >0.99). Both murine and human skin imaging verified that in vivo PpIX fluorescence was detected within 1 hour of applying aminolevulinic acid (ALA) gel. This ultracompact handheld system for quantification of PpIX in skin is well-suited for dermatology clinical workflows. Due to its simplicity and form factor, the proposed system can be readily adapted for use with other smartphone devices and fluorescence imaging applications. Hardware design and software for the system is made freely available on GitHub (https://github.com/optmed/CompactFluorescenceCam).

Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples

Optical spectroscopic techniques have been commonly used to detect the presence of biofilm-forming pathogens (bacteria and fungi) in the agro-food industry. Recently, near-infrared (NIR) spectroscopy revealed that it is also possible to detect the presence of viruses in animal and vegetal tissues. Here we report a platform based on visible and NIR (VNIR) hyperspectral imaging for non-contact, reagent free detection and quantification of laboratory-engineered viral particles in fluid samples (liquid droplets and dry residue) using both partial least square-discriminant analysis and artificial feed-forward neural networks. The detection was successfully achieved in preparations of phosphate buffered solution and artificial saliva, with an equivalent pixel volume of 4 nL and lowest concentration of 800 TU·\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\upmu$$\end{document}μL⁻¹. This method constitutes an innovative approach that could be potentially used at point of care for rapid mass screening of viral infectious diseases and monitoring of the SARS-CoV-2 pandemic.