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Optogenetics presents an alternative method for interfacing with the nervous system over the gold-standard of electrical stimulation. While electrical stimulation requires electrodes to be surgically embedded in tissue for in vivo studies, optical stimulation offers a less-invasive approach that may yield more specific, localized stimulation. The advent of optogenetic laboratory animals—whose motor neurons can be activated when illuminated with blue light—enables research into refining optical stimulation of the mammalian nervous system where subsets of nerve fibers within a nerve may be stimulated without embedding any device directly into the nerve itself. However, optical stimulation has a major drawback in that light is readily scattered and absorbed in tissue thereby limiting the depth with which a single emission source can penetrate. We hypothesize that the use of multiple, focused light emissions deployed around the circumference of a nerve can overcome these light-scattering limitations. To understand the physical parameters necessary to produce pinpointed light stimulation within a single nerve, we employed a simplified Monte Carlo simulation to estimate the size of nerves where this technique may be successful, as well as the necessary optical lens design for emitters to be used during future in vivo studies. By modeling multiple focused beams, we find that only fascicles within a nerve diameter less than 1 mm are fully accessible to focused optical stimulation; a minimum of 4 light sources is required to generate a photon intensity at a point in a nerve over the initial contact along its surface. To elicit the same effect in larger nerves, focusing lenses would require a numerical aperture $$> 1$$ > 1 . These simulations inform on the design of instrumentation capable of stimulating disparate motor neurons in mouse sciatic nerve to control hindlimb movement.

In this paper, we report the development of a wireless, passive, biocompatible, and flexible system for stimulation of human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMS). Fabricated on a transparent parylene/PDMS substrate, the proposed stimulator enables real-time excitation and characterization of hiPSC-CMs cultured on-board. The device comprises a rectenna operating at 2.35 GHz which receives radio frequency (RF) energy from an external transmitter and converts it into DC voltage to deliver monophasic stimulation. The operation of the stimulator was primarily verified by delivering monophasic voltage pulses through gold electrodes to hiPSC-CMs cultured on the Matrigel-coated substrates. Stimulated hiPSC-CMs beat in accordance with the monophasic pulses when delivered at 0.5, 1, and 2 Hz pulsing frequency, while no significant cell death was observed. The wireless stimulator could generate monophasic pulses with an amplitude of 8 V at a distance of 15 mm. These results demonstrated the proposed wireless stimulator's efficacy for providing electrical stimulation to engineered cardiac tissues. The proposed stimulator will have a wide application in tissue engineering where a fully wireless stimulation of electroconductive cells is needed. The device also has potential to be employed as a cardiac stimulator by delivering external stimulation and regulating the contractions of cardiac tissue.

Colorimetric assays are an important tool in point-of-care testing that offers several advantages such as rapid response times and inexpensive costs. A factor that currently limits their use is objective measures to determine results. Current solutions consist of creating a test reader that standardizes the conditions the strip is under before measuring. However, this increases the cost and decreases the portability of these assays. The focus of this study is to train a convolutional neural network (CNN) that can objectively determine results of colorimetric assays under varying conditions. To ensure the flexibility of the model to several types of colorimetric assays, three models are trained on the same CNN. The images these models are trained on consist of positive and negative images of ETG (99.87% positive classification, 99.96% negative classification), fentanyl (99.60% positive classification, 99.56% negative classification), and HPV antibody (99.86% positive classification, 100% negative classification) strips taken under different lighting and background conditions. A fourth model is trained on an image set composed of all three strip types with the lowest classification accuracy being 99.11%.

The application of microfluidics in Point of Care (PoC) testing was a breakthrough in PoC diagnostics, yet high precision testing remains a challenge. In order to extract and isolate pure RNA or DNA from biofluids containing a virus or virion, small spherical magnetic particles called magnetic beads are commonly used in laboratories. Magnetic beads have many applications ranging from purification of nucleic acids, magnetic cell separation, targeted drug delivery to brain or malignant tumors, magnetic chaining etc. Unfortunately, integrating magnetic beads into PoC devices is challenging. This paper delves into a comparative study of the behaviour and parameters of five different sizes of carboxyl coated paramagnetic beads along with silica coated dynabeads. Their behavior is characterized in a microcapillary channel for a SARS-CoV-2 virus PoC testing kit to enrich the sample, concentrating the nucleic acid. This step would increase the sensitivity and specificity for any nucleic acid-based PoC testing device.

Ammonium nitrate and nitromethane are two of the most prevalent ingredients in improvised explosive devices (IED). Developing a detection system for IEDs in open public events where no specific check points are available requires many large scale, fine-grained simulations to estimate the explosive vapors. However, such large scale molecular simulations at the required granularity is very time consuming and in most cases not feasible. In this paper, we propose region-specific meshing to alleviate the computational cost. The proposed simulation methodology provides accurate results as compared with a baseline simulation of fine grained mesh (in a small area) while providing significant reduction in simulation time. Thus, large scale simulations at feasible computational burden can be achieved.

Thin-film microelectrode arrays have a wide variety of applications in research and medical devices. Conventionally, these arrays are fabricated through the use of photolithography, which can be problematic for innovative medical device fabrication due to long process times, inflexibility to design changes, and the reliance on potentially harmful chemicals. Here, we present the use of laser micromachining as an alternative to photolithography processes to fabricate thin-film polyimide microelectrode arrays. This fabrication method lends itself to an iterative design process as it can reduce fabrication steps and is attractive for medical devices since it can be used without harmful chemicals. Several process parameters were explored and the performance of the fabricated electrodes was compared to similar electrodes that were fabricated with conventional photolithography processes.

Point-of-care (PoC) testing systems aim to bring affordable and convenient diagnostics to resource limited locations. In our previous work in detecting human papilloma virus (HPV) via lateral flow immunoassays and fluorescence detection, we determined that the performance of the assay depends on the temperature and humidity. Thus, we need to maintain a fixed environment for the assay to produce reliable results. Therefore, we define the need for a portable, climate-controlled chamber for field work in low resource settings. By combining low-cost electronics and household items, a simple feedback loop is designed to regulate the internal conditions of the testing environment. The ability of our chamber to maintain a desired climate will be tested for accuracy and stability to ensure that it is competent for in-field usage.

We present a novel 3D printed Microfluidic Actuation System for lateral flow assay in low resource settings. The system is used to deliver reagents for multi-step assays from blisters placed into cavities in the 3D printed assembly. The system is operated by manually depressing the blister housing and rotating to the next blister location. This is repeated for each step in the assay to enable a simple and repeatable method of delivering specified volumes to the assay at arbitrary time intervals as required by the assay. The blisters provide for robust storage while maintaining consistent aliquots for the assay. We characterize the percent of the total volume delivered to the lateral flow assay from the blisters including the volume dispensed at given time intervals.

We previously reported a fluorescence-based Point-of-care (PoC) diagnostic for human papillomavirus (HPV). In this work, we present our progress in modifying the system for colorimetric testing. This decreases the number of steps required to complete the assay, simplifies calibration, and decreases the cost of the system. We were able to confirm the system was successfully modified for colorimetric detection using a newly designed 3D printed cartridge and calibration slides.

Lateral Flow Immunoassays (LFIAs) are among the most successful Point of Care (POC) tests. However, factors like reagent stability, reaction rates, and binding kinetics limit the performance and robustness of LFIAs. One of the factors that affects the overall performance of LFIA is the fluid flow rate, and hence, it is desirable to maintain a predictable fluid velocity in porous media. The main objective of this study is to build a statistical model that estimates the fluid velocity in porous media for any given ambient condition to enable us to determine the optimal design parameters for achieving a desired fluid velocity in porous media.

In this work, we offer a high level view of the difference in performance of three circuit architectures for estimating slowly changing current: the transimpedance amplifier, linear integrator, and integrate and fire. When considering a portable or IoT (Internet of Things) using a microprocessor-based system, we determine architecture trade-offs in performance fo a low-cost implementation. Given the constraints and capabilities of available microprocessor technologies, we provide a comparative analysis of the different architectures’ strengths and weaknesses.

While Volatile Organic Compounds (VOC) and ammonia have a place in our daily lives, their leakage into the environment is harmful to human health. In order to prevent and detect gaseous leaks of harmful VOCs, a cyber-physical system (CPS) comprised of ordinary people or first responders is proposed. This CPS uses small, low-cost sensors coupled to smart phones or mobile devices with the necessary computation and communication capabilities. The efficacy of such a CPS hinges on its ability to address technical challenges stemming from the fact that identically produced sensors may produce different results under the same conditions due to sensor drift, noise, or resolution errors.The proposed system makes use of time-varying signals produced by sensors to detect gas leaks. Sensors sample the gas vapor level in a continuous manner and time-varying sensor data is processed using deep neural networks. One of the neural networks (NN) is an energy efficient Additive Neural Network (AddNet) which can be implemented in host devices. The second NN is the discriminator of a GAN and the third a regular convolutional NN. AddNet produces comparable VOC gas leak detection results to regular convolutional networks while reducing area requirements by two thirds.

This paper presents a new concept combining flexible organic light-emitting diode (OLED) display technology with fluorescent biorecognition microarray technology to fabricate point-of-care immunobiosensors. Our approach is designed to leverage commercial OLED display technology to reduce pre-functionalized biosensor substrate costs to pennies per ${cm}^{2}$ combined with leveraging the display industries ability to manufacture an immense number of low-cost consumer electronic products annually. For this work, we demonstrate that our new approach using high brightness flexible OLED display technology combined with a charge integrating readout circuit and optical filters can offer point-of-care diagnostic sensitivity at or below 10 pg/mL, which approaches the lower limit of detection (LLOD) of typical clinical laboratory instrumentation.

We present a low-cost fluorescence and colorimetry label detection platform for point-of-care (POC) applications. Our platform is designed to deliver clinical level diagnostic sensitivity. It improves the performance of the traditional lateral flow assay (LFA) by decreasing the detection limit by 3 orders of magnitude and enabling quantitative detection of analytes. In this work, we characterize the fluorescence detection platform and detail the effects of label selection on the overall system performance. The effects of optoelectronic configuration, brightness, and spectral matching are presented. Finally, we demonstrate the utility of our platform for colorimetric detection and compare its performance to a standard central laboratory microplate reader. The limit-of-detection (LOD) for our point-of-care platform was determined to be the same as the microplate reader, detecting 2 × 104 0.5 µm microspheres without the use of focusing or transfer optics.

Stimulation has been a key technique for studying underlying mechanisms of the nervous system. Electrical stimulation has been the predominant method for eliciting desired muscle responses for decades, yet methodologies remain invasive and low in selectivity of tissue stimulated. Current injection affects all local tissue types and can lead to damaging immune responses that threaten both nerves and equipment alike. Optogenetics provides a solution for such stimulation difficulties by increasing specificity and decreasing risk to tissue. Via genetic modifications, opsins (light-sensitive proteins) are added to neurons, and can be activated by light to cause neuron excitation. Through preliminary in vivo testing in transgenic mice expressing channelrhodopsin (ChR2) we validate that multiple beams of light have an additive effect and increase the response from muscles innervated by the target nerve. Measuring hindlimb flexion increases with increase in number of light sources present. To further characterize this additive effect, a Monte Carlo computer model was generated to simulate a random-walk of photons passing through nerve tissue. The model shows that light beams can aggregate within the nerve, although are limited. When using collimated light, multiple beams converging on the interior region of the nerve cannot result in a higher intensity than outermost layer of tissue nearest a single light source. This model serves as a tool to aid future animal studies by determining light emission parameters, specifically prescribing the need for optically-focused light, when attempting to selectively stimulate regions deep in the interior of a given nerve. Such capability will allow for high spatial resolution of stimulation in peripheral nerves giving finer control of excitation in downstream tissue.

The growing market for wearable, portable, and IoT devices has generated a need for a class of circuits to meet the requirements for these applications. In this work we specifically investigate ammeters. The design space requires low component count circuits for measuring slowly varying currents using low-cost microcontrollers. Simple architectures, feasible for an electronics novice are described and compared experimentally. The use of the time domain to improve error and range of measurement is considered. This guide provides an individual without extensive electronics design experience with a simple selection guide for choosing the appropriate architecture for their specific application.

Point-of-care medical diagnostics can provide efficient, cost-effective medical care, and have the potential to fundamentally change our current approach to global health. There have been substantial efforts in developing lateral flow assays for serologic testing, but most of the existing approaches have limited portability, are expensive, and offer limited analytical sensitivity. In this paper, we demonstrated an assay for the detection of antibodies in plasma to Epstein-Barr Nuclear Antigen-1 (EBNA-1) protein and optimization of the assay including washing and blocking conditions. We also investigated the effect of the storage on the assay strips. Using our optimized conditions, we were able to detect anti-Human Papilloma Virus (HPV)-16 E7 antibodies after three weeks of storage. Our goal is to adapt this system to detect HPV biomarkers for cervical cancers in low and middle-income countries.

Fluorescence- based lateral flow immunoassays (LFIAs) remain relatively unexplored compared to colorimetric LFIAs for point-of-care (PoC) disease diagnosis and health monitoring. For fluorescence-based LFIAs, a major challenge includes the auto-fluorescence of the nitrocellulose and nonspecific binding of fluorescent polystyrene microspheres. In this paper, we aim to characterize antibody-microsphere conjugates in a fluorescence-based serological assay on nitrocellulose. Factors such as coating concentration and quantity of microspheres were considered and their impacts on nonspecific binding and signal-to-noise ratio are discussed. Finally, we use the determined conditions for the antibody-microsphere conjugates to demonstrate the sensitivity of a proof-of-concept assay detecting antibodies to Epstein-Barr Nuclear Antigen-1 in pooled human plasma samples. A titration of the seropositive plasma samples demonstrated a titer approaching 1:1,000 using only 30 μL of diluted sample and a sample-to-result time of less than one hour.

Arizona State University (ASU) established an NSF Research Experiences for Undergraduates (REU) site to embed students in research projects related to integrated sensor and signal processing systems. The program includes both sensor hardware and algorithm/software design for a variety of applications including health monitoring. The site was funded in February 2017 and the Co-PIs recruited nine students from different universities and community colleges to spend the summer of 2017 in research laboratories at ASU. The program included structured training with modules in sensor design, signal processing, and machine learning. Cross-cutting training included research ethics, IEEE manuscript development, and building presentation skills. Nine undergraduate research projects were launched and the program went through an assessment by an independent evaluator. This paper describes the REU activities, modules, training, projects, and their assessment.

The work presents implementing a low cost pH sensing system for biological applications in a flexible electronics process. As a part of the system the work describes an ion sensitive field effect transistor, using indium tin oxide (ITO) as a sensing layer and gold as a reference electrode, on a flexible substrate. The devices presented here are designed and fabricated using the thin film transistor (TFT) display technology at the Arizona State University Flexible Electronics and Display Center. It was observed that ITO has a sensitivity of 50 mV/pH. The work also discusses the variability in these devices and signal processing that could be used to calibrate them. Toward this end, a readout circuit designed in a 0.5 μm CMOS process is presented to interface with the sensors.

This paper demonstrates a self-powered Maximum Power Direction Tracking (MPDT) system capable of maximizing the energy harvesting by automatically adjusting the angle of the solar panel. The whole system is powered by a solar panel so no extra power supply is needed. The entire system consists of a solar panel, a motor, and a CMOS chip. A novel light direction sensor and the needed circuit are integrated in a single chip which is fabricated by a standard 0.5 μm CMOS process. So it is small-size and low-cost. The system was tested to verify performance with different light direction and intensity. The results show that the system has good sensitivity to the incident angle and achieve tracking accuracy of ± 1.8 ° over a optical power range of 30–110 mW / cm 2 . The presented system obtains an average output power gain of 18.4% over the fixed southwards mounted system under real weather conditions.

Point-of-Care (PoC) diagnostic devices, such as lateral flow tests, are often used in low and middle-income countries (LMIC) for low-cost disease detection. Most commercial lateral flow tests use colorimetric detection on a nitrocellulose substrate. In this paper, we present a multistep, fluorescence-based assay detection system, which can detect antibodies in plasma to recombinant protein. Fluorescence-based detection allows us to achieve higher sensitivity, while a nitrocellulose substrate enables fluid handling, high protein immobilization, rapid detection time, and affordability. As a proof-of-concept for detection of disease-specific biomarkers in plasma, we demonstrate the detection of antibodies in plasma to Epstein-Barr nuclear antigen-1 (EBNA-1) recombinant protein and to human papillomavirus (HPV) 16 E7 recombinant protein. We show that our detection system is able to detect EBNA-1-specific antibodies at a 1:10,000 plasma dilution and HPV 16 E7-specific antibodies at a 1:5,000 plasma dilution, indicating high sensitivity. This platform is a low-cost device that can detect fluorescence from labeled biomarkers on a lateral flow assay. Ultimately, we aim to adapt this system to detect HPV 16 and 18 biomarkers for cervical cancer screening in LMICs.