Integrating optical and electrical sensing with machine learning for advanced particle characterization.

Particle classification plays a crucial role in various scientific and technological applications, such as differentiating between bacteria and viruses in healthcare applications or identifying and classifying cancer cells. This technique requires accurate and efficient analysis of particle properties. In this study, we investigated the integration of electrical and optical features through a multimodal approach for particle classification. Machine learning classifier algorithms were applied to evaluate the impact of combining these measurements. Our results demonstrate the superiority of the multimodal approach over analyzing electrical or optical features independently. We achieved an average test accuracy of 94.9% by integrating both modalities, compared to 66.4% for electrical features alone and 90.7% for optical features alone. This highlights the complementary nature of electrical and optical information and its potential for enhancing classification performance. By leveraging electrical sensing and optical imaging techniques, our multimodal approach provides deeper insights into particle properties and offers a more comprehensive understanding of complex biological systems.

A computer vision enhanced smart phone platform for microfluidic urine glucometry.

Glucose is an important biomarker for diagnosing and prognosing various diseases, including diabetes and hypoglycemia, which can have severe side effects, symptoms, and even lead to death in patients. As a result, there is a need for quick and economical glucose level measurements to help identify those at potential risk. With the increase in smartphone users, portable smartphone glucose sensors are becoming popular. In this paper, we present a disposable microfluidic glucose sensor that accurately and rapidly quantifies glucose levels in human urine using a combination of colorimetric analysis and computer vision. This glucose sensor implements a disposable microfluidic device based on medical-grade tapes and glucose analysis strips on a glass slide integrated with a custom-made polydimethylsiloxane (PDMS) micropump that accelerates capillary flow, making it economical, convenient, rapid, and equipment-free. After absorbing the target solution, the disposable device is slid into the 3D-printed main chassis and illuminated exclusively with Light Emitting Diode (LED) illumination, which is pivotal to color-sensitive experiments. After collecting images, the images are imported into the algorithm to measure the glucose levels using computer vision and average RGB values measurements. This article illustrates the impressive accuracy and consistency of the glucose sensor in quantifying glucose in sucrose water. This is evidenced by the close agreement between the computer vision method used by the sensor and the traditional method of measuring in the biology field, as well as the small variation observed between different sensor performances. The exponential regression curve used in the study further confirms the strong relationship between glucose concentrations and average RGB values, with an R-square value of 0.997 indicating a high degree of correlation between these variables. The article also emphasizes the potential transferability of the solution described to other types of assays and smartphone-based sensors.

A two-minute assay for electronic quantification of antibodies in saliva enabled through a reusable microfluidic multi-frequency impedance cytometer and machine learning analysis.

The use of saliva as a diagnostic fluid has always been appealing due to the ability for rapid and non-invasive sampling for monitoring health status and the onset and progression of disease and treatment progress. Saliva is rich in protein biomarkers and provides a wealth of information for diagnosis and prognosis of various disease conditions. Portable electronic tools which rapidly monitor protein biomarkers would facilitate point-of-care diagnosis and monitoring of various health conditions. For example, the detection of antibodies in saliva can enable rapid diagnosis and tracking disease pathogenesis of various auto-immune diseases like sepsis. Here, we present a novel method involving immuno-capture of proteins on antibody coated beads and electrical detection of dielectric properties of the beads. The changes in electrical properties of a bead when capturing proteins are extremely complex and difficult to model physically in an accurate manner. The ability to measure impedance of thousands of beads at multiple frequencies, however, allows for a data-driven approach for protein quantification. By moving from a physics driven approach to a data driven approach, we have developed, for the first time ever to the best of our knowledge, an electronic assay using a reusable microfluidic impedance cytometer chip in conjunction with supervised machine learning to quantifying immunoglobulins G (IgG) and immunoglobulins A (IgA) in saliva within two minutes.

Cell phone microscopy enabled low-cost manufacturable colorimetric urine glucose test.

Glucose serves as a pivotal biomarker crucial for the monitoring and diagnosis of a spectrum of medical conditions, encompassing hypoglycemia, hyperglycemia, and diabetes, all of which may precipitate severe clinical manifestations in individuals. As a result, there is a growing demand within the medical domain for the development of rapid, cost-effective, and user-friendly diagnostic tools. In this research article, we introduce an innovative glucose sensor that relies on microfluidic devices meticulously crafted from disposable, medical-grade tapes. These devices incorporate glucose urine analysis strips securely affixed to microscope glass slides. The microfluidic channels are intricately created through laser cutting, representing a departure from traditional cleanroom techniques. This approach streamlines production processes, enhances cost-efficiency, and obviates the need for specialized equipment. Subsequent to the absorption of the target solution, the disposable device is enclosed within a 3D-printed housing. Image capture is seamlessly facilitated through the use of a smartphone camera for subsequent colorimetric analysis. Our study adeptly demonstrates the glucose sensor's capability to accurately quantify glucose concentrations within sucrose solutions. This is achieved by employing an exponential regression model, elucidating the intricate relationship between glucose concentrations and average RGB (Red-Green-Blue) values. Furthermore, our comprehensive analysis reveals minimal variation in sensor performance across different instances. Significantly, this study underscores the potential adaptability and versatility of our solution for a wide array of assay types and smartphone-based sensor systems, making it particularly promising for deployment in resource-constrained settings and undeveloped countries. The robust correlation established between glucose concentrations and average RGB values, substantiated by an impressive R-square value of 0.98709, underscores the effectiveness and reliability of our pioneering approach within the medical field.

Biosensors and machine learning for enhanced detection, stratification, and classification of cells: a review.

Biological cells, by definition, are the basic units which contain the fundamental molecules of life of which all living things are composed. Understanding how they function and differentiating cells from one another, therefore, is of paramount importance for disease diagnostics as well as therapeutics. Sensors focusing on the detection and stratification of cells have gained popularity as technological advancements have allowed for the miniaturization of various components inching us closer to Point-of-Care (POC) solutions with each passing day. Furthermore, Machine Learning has allowed for enhancement in the analytical capabilities of these various biosensing modalities, especially the challenging task of classification of cells into various categories using a data-driven approach rather than physics-driven. In this review, we provide an account of how Machine Learning has been applied explicitly to sensors that detect and classify cells. We also provide a comparison of how different sensing modalities and algorithms affect the classifier accuracy and the dataset size required.

A Smartphone-Based Disposable Hemoglobin Sensor Based on Colorimetric Analysis.

Hemoglobin is a biomarker of interest for the diagnosis and prognosis of various diseases such as anemia, sickle cell disease, and thalassemia. In this paper, we present a disposable device that has the potential of being used in a setting for accurately quantifying hemoglobin levels in whole blood based on colorimetric analysis using a smartphone camera. Our biosensor employs a disposable microfluidic chip which is made using medical-grade tapes and filter paper on a glass slide in conjunction with a custom-made PolyDimethylSiloaxane (PDMS) micropump for enhancing capillary flow. Once the blood flows through the device, the glass slide is imaged using a smartphone equipped with a custom 3D printed attachment. The attachment has a Light Emitting Diode (LED) that functions as an independent light source to reduce the noise caused by background illumination and external light sources. We then use the RGB values obtained from the image to quantify the hemoglobin levels. We demonstrated the capability of our device for quantifying hemoglobin in Bovine Hemoglobin Powder, Frozen Beef Blood, and human blood. We present a logarithmic model that specifies the relationship between the Red channel of the RGB values and Hemoglobin concentration.

Functionalization of hybrid surface microparticles for in vitro cellular antigen classification.

Hybrid material surfaces on microparticles are emerging as vehicles for many biomedical multiplexing applications. Functionalization of these hybrid surface microparticles to biomolecules presents unique challenges related to optimization of surface chemistries including uniformity, repeatability, and sample sparring. Hybrid interfaces between microlevel surfaces and individual biomolecules will provide different microenvironments impacting the surface functionalization optimization and efficiency. Here, we propose and validate the first demonstration of streptavidin adsorption-based antibody functionalization on unmodified, hybrid surface microparticles for in vitro analysis. We test this analytical technique and fabricate hybrid surface microparticles with a polystyrene core and aluminum oxide semi-coating. Additionally, we optimize the streptavidin-biotin functionalization chemistry in both assay implementation and sample sparring via analytical mass balances for these microparticles and subsequently conjugate anti-human CD11b antibodies. Result confirmation and characterization occurs from ultraviolet protein absorbance and ImageJ processing of fluorescence microscopy images. Additionally, we design and implement the multi-sectional imaging (MSI) approach to support functionalization uniformity on the hybrid surface microparticles. Finally, as a proof-of-concept performance, we validate anti-CD11b antibodies functionalization by visualizing hybrid surface microparticles conjugate to human neutrophils isolated from blood samples collected from potentially septic patients. Our study introduces and defines a category of functionalization for hybrid surface microparticles with the intent of minuscule sample volumes, low cost, and low environmental impact to be used for many cellular or proteomic in vitro multiplexing applications in the future. Graphical abstract.

Potential Microfluidic Devices for COVID-19 Antibody Detection at Point-of-Care (POC): A Review.

COVID-19 has been declared a global pandemic which has brought the world economy and the society to a standstill. The current emphasis of testing is on detection of genetic material of SARS-CoV-2. Such tests are useful for assessing the current state of a subject: Infected or not infected. In addition to such tests, antibody testing is necessary to stratify the population into three groups: never exposed, infected, and immune. Such a stratification is necessary for safely reopening the society and remobilizing the economy. The aim of this review article is to inform the audience of the current diagnostic and surveillance technologies that are being employed for the detection of SARS-CoV-2 antibodies along with their shortcomings, and to highlight microfluidic sensors and devices that show promise of being commercialized for detection and quantification of SARS-CoV-2 antibodies in low-resource and Point-of-Care (POC) settings.

A ten-minute, single step, label-free, sample-to-answer assay for qualitative detection of cytokines in serum at femtomolar levels.

Label-free electronic affinity based immuno-sensing is an attractive candidate as a platform technology for analyzing biomarkers due to the ease of miniaturization and minimal use of reagents. Electronic based sensing approaches, however, have lagged behind their optical counterparts in terms of detection limit, selectivity, and reliability. Also, the matrix dependent nature of electronic sensing modalities makes difficult the analysis of biomarkers in high salt concentration samples such as serum due to charge screening. We present a novel sensing platform, the micro-well sensor, that works by functionalizing nanoscale volume wells with antibodies and monitoring the impedance change inside the wells due binding of target protein. This detection modality is advantageous to many label-free electronic sensors in that signal power scales with increase in salt concentration, thus improving the sensitivity of the platform. We demonstrate rapid label-free qualitative detection of cytokines within ten minutes at femtoMolar concentrations and a dynamic range of 3 orders of magnitude in serum samples. We describe the design, fabrication, and characterization of the micro-well sensor in serum samples using inflammatory protein biomarkers.

Improved Precision in Surface-Enhanced Raman Scattering Quantification of Analyte through Dual-Modality Multisite Sensing.

Accurate quantification of analyte using surface-enhanced Raman spectroscopy (SERS) is a desired, yet unfulfilled, ability that could enable a plethora of diagnostic- and defense-related applications. The major hurdles to overcome to achieve this goal are expensive manufacturing for highly ordered and reproducible substrates and low reproducibility of substrates produced through low cost methods. A technology that can set industry standards for manufacturing/processing of SERS substrates is still yet to be achieved. A dual-modality multisite sensing approach was developed, that overcomes the limitations experienced when fabricating bottom-up, reproducible, sensitive, and low-cost SERS substrates. Electrochemistry was combined with SERS for dual-modality sensing to improve precision by adding redundancy and encoding features, thus increasing measurement robustness and predictability. This technique works by calibrating SERS response with respect to active surface area, a parameter known to be proportional to charge, which can be estimated via electrochemical measurements. The dual-modality multisite measurement demonstrates at least 2.8× improvement in assay precision compared to the traditional single-site Raman measurements. The technique yields overall improved precision of measurement and is not limited to any particular SERS substrate or geometry, and thus it can be adapted and incorporated readily in any SERS sensing assay.

Cytocoded passwords: BioMEMS based barcoding of biological samples for user authentication in microfluidic diagnostic devices.

Smart and connected point-of-care (POC) medical devices are becoming ever more ubiquitous and have the potential to radically improve disease diagnosis and health monitoring. This emerging connectivity can potentially create serious security issues where patient privacy can be easily compromised. Protection of patient data from malicious cyber-physical attackers requires radical solutions at the BioMEMS level. Ideally, the information exchange between the patient and practitioner is an automated and transparent process for the patient. In practice, this exchange requires both the patient and the test results to be authenticated and validated respectively on the storage service to ensure that the medical diagnostic results are properly stored and their access is protected. This secure authentication phase is particularly critical for medical diagnostics: patient data exposure could lead to negative social effects. This work focuses on providing a transparent authentication mechanism for patient blood tests performed using impedance flow cytometry. The goal is twofold: first, to alleviate the user from security procedures, precisely an authentication step, while using the medical device; second, to provide a unique identifier for the test results when stored in a remote server. This paper describes a domain specific authentication method for impedance flow cytometry devices. We spike into the blood samples synthetic micro-beads of different sizes, at determined concentrations, to generate a unique authentication string that uniquely identify a test result on the remote storage service. These authentication strings are embedded in the test devices and can be used as a convenient alternative to generic authentication methods, such as logins and passwords. This alternative method removes the authentication burden from the user and protects patient's privacy further by preventing them from linking their personal information to their test results.

Tunable control of antibody immobilization using electric field.

The controlled immobilization of proteins on solid-state surfaces can play an important role in enhancing the sensitivity of both affinity-based biosensors and probe-free sensing platforms. Typical methods of controlling the orientation of probe proteins on a sensor surface involve surface chemistry-based techniques. Here, we present a method of tunably controlling the immobilization of proteins on a solid-state surface using electric field. We study the ability to orient molecules by immobilizing IgG molecules in microchannels while applying lateral fields. We use atomic force microscopy to both qualitatively and quantitatively study the orientation of antibodies on glass surfaces. We apply this ability for controlled orientation to enhance the performance of affinity-based assays. As a proof of concept, we use fluorescence detection to indirectly verify the modulation of the orientation of proteins bound to the surface. We studied the interaction of fluorescently tagged anti-IgG with surface immobilized IgG controlled by electric field. Our study demonstrates that the use of electric field can result in more than 100% enhancement in signal-to-noise ratio compared with normal physical adsorption.

A portable battery powered microfluidic impedance cytometer with smartphone readout: towards personal health monitoring.

We present a portable system for personalized blood cell counting consisting of a microfluidic impedance cytometer and portable analog readout electronics, feeding into an analog-to-digital converter (ADC), and being transmitted via Bluetooth to a user-accessible mobile application. We fabricated a microfluidic impedance cytometer with a novel portable analog readout. The novel design of the analog readout, which consists of a lock-in-amplifier followed by a high-pass filter stage for subtraction of drift and DC offset, and a post-subtraction high gain stage, enables detection of particles and cells as small as 1 µm in diameter, despite using a low-end 8-bit ADC. The lock-in-amplifier and the ADC were set up to receive and transmit data from a Bluetooth module. In order to initiate the system, as well as to transmit all of the data, a user friendly mobile application was developed, and a proof-of-concept trial was run on a blood sample. Applications such as personalized health monitoring require robust device operation and resilience to clogging. It is desirable to avoid using channels comparable in size to the particles being detected thus requiring high levels of sensitivity. Despite using low-end off-the-shelf hardware, our sensing platform was capable of detecting changes in impedance as small as 0.032%, allowing detection of 3 µm diameter particles in a 300 µm wide channel. The sensitivity of our system is comparable to that of a high-end bench-top impedance spectrometer when tested using the same sensors. The novel analog design allowed for an instrument with a footprint of less than 80 cm2. The aim of this work is to demonstrate the potential of using microfluidic impedance spectroscopy for low cost health monitoring. We demonstrated the utility of the platform technology towards cell counting, however, our platform is broadly applicable to assaying wide panels of biomarkers including proteins, nucleic acids, and various cell types.

Digital microfluidic assay for protein detection.

Global studies of the human proteome have revealed a plethora of putative protein biomarkers. However, their application for early disease detection remains at a standstill without suitable methods to realize their utility in the clinical setting. There thus continues to be tremendous interest in developing new technology for sensitive protein detection that is both low in cost and carries a small footprint to be able to be used at the point of care. The current gold standard method for protein biomarker detection is the ELISA, which measures protein abundance using bulky fluorescent scanners that lack portability. Here, we present a digital microfluidic platform for protein biomarker detection that is low in cost compared with standard optical detection methods, without any compromise in sensitivity. This platform furthermore makes use of simple electronics, enabling its translation into a portable handheld device, and has been developed in a manner that can easily be adapted to assay different types of proteomic biomarkers. We demonstrate its utility in quantifying not only protein abundance, but also activity. Interleukin-6 abundance could be assayed from concentrations as low as 50 pM (an order of magnitude lower than that detectable by a comparable laboratory designed ELISA) using less than 5 µL of sample, and Abelson tyrosine kinase activity was detectable in samples containing 100 pM of kinase.

Portable Cytometry Using Microscale Electronic Sensing.

In this manuscript, we present three different micro-impedance sensing architectures for electronic counting of cells and beads. The first method of sensing is based on using an open circuit sensing electrode integrated in a micro-pore, which measures the shift in potential as a micron-sized particle passes through. Our micro-pore, based on a funnel shaped microchannel, was fabricated in PDMS and was bound covalently to a glass substrate patterned with a gold open circuit electrode. The amplification circuitry was integrated onto a battery-powered custom printed circuit board. The second method is based on a three electrode differential measurement, which opens up the potential of using signal processing techniques to increase signal to noise ratio post measurement. The third architecture uses a contactless sensing approach, which significantly minimizes the cost of the consumable component of the impedance cytometer. We demonstrated proof of concept for the three sensing architectures by measuring the detected signal due to the passage of micron sized beads through the pore.

PicoMolar level detection of protein biomarkers based on electronic sizing of bead aggregates: theoretical and experimental considerations.

We demonstrate a novel method for electronically detecting and quantifying protein biomarkers using microfluidic impedance cytometry. Our biosensor, which consists of gold electrodes micro-fabricated in a microchannel, detects the differences between bead aggregates of varying sizes in a micro-pore sandwiched between two micro channels. We perform a sandwich immunoassay, where the complementary antibody pairs are immobilized on two different bead types, and the presence of antigen results in bead aggregation, the amount of which depends on antigen quantity. When single beads or bead aggregates pass through the impedance sensor, differences in impedance change are detected. In this manuscript, we perform a comprehensive theoretical study on the limits imposed on sensitivity of this technique due to electronic noise and also mass transfer and reaction limits. We also experimentally characterize the performance of this technique by validating the technique on an IgG detection assay. A detection limit at the picoMolar level is demonstrated, thus comparable in sensitivity to a sandwich ELISA.

Nanoelectronic impedance detection of target cells.

Detection of cells is typically performed using optical fluorescence based techniques such as flow cytometry. Here we present the impedance detection of target cells using a nanoelectronic probe we have developed, which we refer to as the nanoneedle biosensor. The nanoneedle consists of a thin film conducting electrode layer at the bottom, an insulative oxide layer above, another conductive electrode layer above, and a protective oxide above. The electrical impedance is measured between the two electrode layers. Cells captured on the surface of the nanoneedle tip results in a decrease in the impedance across the sensing electrodes. The basic mechanisms behind the electrical response of cells in solution under an applied alternating electrical field stems from modulation of the relative permittivity at the interface. In this paper we discuss, the circuit model, the nanofabrication, and the testing and characterization of the sensor. We demonstrate proof of concept for detection of yeast cells with specificity. We envision the sensor presented in this paper to be combined with microfluidic pre-concentration technologies to develop low cost point-of-care diagnostic assays for the clinical setting.

High Sensitivity and High Throughput Magnetic Flow CMOS Cytometers with 2D Oscillator Array and Inter-Sensor Spectrogram Cross-correlation.

In the paper, we present an integrated flow cytometer with a 2D array of magnetic sensors based on dual-frequency oscillators in a 65-nm CMOS process, with the chip packaged with microfluidic controls. The sensor architecture and the presented array signal processing allows uninhibited flow of the sample for high throughput without the need for hydrodynamic focusing to a single sensor. To overcome the challenge of sensitivity and specificity that comes as a trade off with high throughout, we perform two levels of signal processing. First, utilizing the fact that a magnetically tagged cell is expected to excite sequentially an array of sensors in a time-delayed fashion, we perform inter-site cross-correlation of the sensor spectrograms that allows us to suppress the probability of false detection drastically, allowing theoretical sensitivity reaching towards sub-ppM levels that is needed for rare cell or circulating tumor cell detection. In addition, we implement two distinct methods to suppress correlated low frequency drifts of singular sensors-one with an on-chip sensor reference and one that utilizes the frequency dependence of the susceptibility of super-paramagnetic magnetic beads that we deploy as tags. We demonstrate these techniques on a 7×7 sensor array in 65 nm CMOS technology packaged with microfluidics with magnetically tagged dielectric particles and cultu lymphoma cancer cells.

Clinical evaluation of a fully electronic microfluidic white blood cell analyzer.

The White Blood Cell (WBC) count is one of the key parameters signaling the health of the immune system. Abnormal WBC counts often signal a systemic insult to the body such as an underlying infection or an adverse side effect to medication. Typically, the blood collected is sent to a central lab for testing, and results come back within hours, which is often inconvenient and may delay time-sensitive diagnosis or treatment. Here, we present the CytoTracker, a fully electronic, microfluidic based instant WBC analyzer with the potential to be used at point-of-care. The CytoTracker is a lightweight, portable, affordable platform capable of quantifying WBCs within minutes using only 50 µl of blood (approximately one drop of blood). In this study, we clinically evaluated the accuracy and performance of CytoTracker in measuring WBC and granulocyte counts. A total of 210 adult patients were recruited in the study. We validated the CytoTracker against a standard benchtop analyzer (Horiba Point of Care Hematology Analyzer, ABX Micros 60). Linear dynamic ranges of 2.5 k/µl- 35 k/µl and 0.6 k/µl- 26 k/µl were achieved for total WBC count and granulocyte count with correlation coefficients of 0.97 and 0.98. In addition, we verified CytoTracker's capability of identifying abnormal blood counts with above 90% sensitivity and specificity. The promising results of this clinical validation study demonstrate the potential for the use of the CytoTracker as a reliable and accurate point-of-care WBC analyzer.