Rapid and Low-Cost Detection of Human Corona Virus Using MEMS ATR-FTIR Spectroscopy

The conventional methods used for the diagnostics of viral infection are either expensive and time-consuming or not accurate enough and dependent on consumable reagents. In the presence of pandemics, a fast and reagent-free solution is needed for mass screening. Recently, the diagnosis of viral infections using infrared spectroscopy has been reported as a fast and low-cost method. In this work a fast and low-cost solution for corona viral detection using infrared spectroscopy based on a compact micro-electro-mechanical systems (MEMS) device and artificial intelligence (AI) suitable for mass deployment is presented. Among the different variants of the corona virus that can infect people, 229E is used in this study due to its low pathogeny. The MEMS ATR-FTIR device employs a 6 reflections ZnSe crystal interface working in the spectral range of 2200-7000 cm-1. The virus was propagated and maintained in a medium for long enough time then cell supernatant was collected and centrifuged. The supernatant was then transferred and titrated using plaque titration assay. Positive virus samples were prepared with a concentration of 105 PFU/mL. Positive and negative control samples were applied on the crystal surface, dried using a heating lamp and the spectrum was captured. Principal component analysis and logistic regression were used as simple AI techniques. A sensitivity of about 90 % and a specificity of about 80 % were obtained demonstrating the potential detection of the virus based on the MEMS FTIR device. © 2023 SPIE.

A Novel Packaging of the MEMS Gas Sensors Used for Harsh Outdoor and Human Exhale Sampling Applications.

Dust or condensed water present in harsh outdoor or high-humidity human breath samples are one of the key sources that cause false detection in Micro Electro-Mechanical System (MEMS) gas sensors. This paper proposes a novel packaging mechanism for MEMS gas sensors that utilizes a self-anchoring mechanism to embed a hydrophobic polytetrafluoroethylene (PTFE) filter into the upper cover of the gas sensor packaging. This approach is distinct from the current method of external pasting. The proposed packaging mechanism is successfully demonstrated in this study. The test results indicate that the innovative packaging with the PTFE filter reduced the average response value of the sensor to the humidity range of 75~95% RH by 60.6% compared to the packaging without the PTFE filter. Additionally, the packaging passed the High-Accelerated Temperature and Humidity Stress (HAST) reliability test. With a similar sensing mechanism, the proposed packaging embedded with a PTFE filter can be further employed for the application of exhalation-related, such as coronavirus disease 2019 (COVID-19), breath screening.

Design of a wearable device for respiratory rate monitoring and detection of anomalous values

The main causes of death in the world are cardiovascular diseases, strokes and respiratory diseases, among which the following stand out: chronic obstructive pulmonary disease and respiratory system infections. Regarding pulmonary function measurement technology, spirometry is the reference standard for the diagnosis and evaluation. This test requires specialized equipment that does not allow it to be performed on an outpatient basis or for constant monitoring. For this reason, the doctor must systematically look for the presence of symptoms that may go unnoticed by the patient and that can be attributed to age, sedentary lifestyle, or the fact of smoking. This is why it would be important to be able to constantly monitor breathing in order to identify irregularities in breathing rates that could be indicative of a respiratory condition.The solution proposed in this article is focused on the design of a prototype of a wearable device that allows the monitoring of the respiratory rate. For this prototype feasibility is analyzed using signals from a database. This device will allow this biometric variable to be identified and will notify when it is outside the normal ranges to suggest an airflow test (spirometry) at a possible early stage of a respiratory condition. This instrumentation system will be integrated into the frame of a pair of glasses, specifically positioning the sensor on the nasal platelets.

N/MEMS Biosensors: An Introduction

In the twenty-first century, biosensors have gathered much wider attention than ever before, irrespective of the technology that promises to bring them forward. With the recent COVID-19 outbreak, the concern and efforts to restore global health and well-being are rising at an unprecedented rate. A requirement to develop precise, fast, point-of-care, reliable, easily disposable/reproducible and low-cost diagnostic tools has ascended. Biosensors form a primary element of hand-held medical kits, tools, products, and/or instruments. They have a very wide range of applications such as nearby environmental checks, detecting the onset of a disease, food quality, drug discovery, medicine dose control, and many more. This chapter explains how Nano/Micro-Electro-Mechanical Systems (N/MEMS) can be enabling technology toward a sustainable, scalable, ultra-miniaturized, easy-to-use, energy-efficient, and integrated bio/chemical sensing system. This study provides a deeper insight into the fundamentals, recent advances, and potential end applications of N/MEMS sensors and integrated systems to detect and measure the concentration of biological and/or chemical analytes. Transduction principle/s, materials, efficient designs, including readout technique, and sensor performance are explained. This is followed by a discussion on how N/MEMS biosensors continue to evolve. The challenges and possible opportunities are also discussed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

A Microfluidic Biosensor for Rapid Detection of Covid-19

We have designed, fabricated, and tested a MEMS-based impedance biosensor for accurate and rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) using of clinical samples. The device consists of focusing region that concentrate low quantities of the virus present in the samples to a detectable threshold, trap region hat maximize the captured virus, and detection region to detect the virus with high selectivity and sensitivity, using an array of interdigitated electrodes (IDE) coated with a specific antibody. Changes in the impedance value due to the binding of the SARS-COV-2 antigen to the antibody will indicate positive or negative result. The device was able to detect inactivated SARS-COV-2 antigen present in phosphate buffer saline (PBS) with a concentration as low as 50 TCID50/ml in 30 minutes. In addition, the biosensor was able to detect SARS-COV-2 in clinical samples (swabs) with a sensitivity of 84 TCID50/ml, also in 30 minutes. © 2023 IEEE.

Recent Advances in Sensor Technology for Biomedical Applications: A Review

Sensor technology has become an integral part of the diagnosis, monitoring, therapeutic and surgical areas of medical science. Various sensors like glucose biosensors for diagnosis of diabetes mellitus or fluorescent sensors for gene expression and protein localization have become a common part of the biomedical field. Due to their widespread applications, various advances and improvements have taken place in medical sensor technology which has led to an increase in the ease and accuracy of diagnosis as well as treatment of diseases. This review article aims at studying various novel and innovative developments in biosensors, fibre optic sensors, sensors used for microelectromechanical systems, flexible sensors and wearable sensors. This article also explores new sensing methodologies and techniques in different medical domains like dentistry, robotic surgery and diagnosis of severe life-threatening diseases like cancer and diabetes. Various sensors and systems used for rapid detection of the SARS-CoV-2 virus which is responsible for the COVID-19 pandemic have also been discussed in this article. Comparison of novel sensor-based systems for detection of various medical parameters with traditional techniques is included. Further research is necessary to develop low cost, highly accurate and easy-to-use medical devices with the help of these innovative sensor technologies. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

An intelligent guided-airborne virus detection

Health has recently faced many challenges, including improving a healthy environment and reducing human life's dangers and economic crises. The last pandemic COVID-19 had badly affected survivor sectors with infection and lockdown exigence. Scientists proposed several solutions to reduce the negative impact of a such pandemic by proposing systems for earlier detection of viruses. The use of metamaterials as an emerging technology in the biosensors field allows a high accuracy. This paper presents a method for detecting and capturing airborne viruses using metasurface technology. The goal is to develop a system that can identify and capture these viruses using FET sensors. The accuracy of the detection is tied to the concentration of aerosols. The model proposes a guided flow of aerosols that positively impacts the detection of viruses through the FET biosensor. The simulation results based on Concentration and airflow velocity delays prove the proposed model's performance. © 2022 IEEE.

Methodology of Teaching and Learning for Micro-and Nano-Electronics During the COVID-19 Pandemic Using Online Educational Tools

Worldwide students are having their education disrupted by the 2019 coronavirus disease (COVID-19) pandemic. Due to this, numerous contact courses have recently been moved to the online format in academic reforms. Microelectronics, Nanoelectronics, Nano-Electro-Mechanical Systems (NEMS) and Micro-Electro-Mechanical Systems (MEMS), in general, become challenging to educate and learn for both lecturers and students, respectively in this pandemic scenario. The epidemic has also offered a stimulus to increase the use of educational tools. The primary goal is to use Project-Based Learning (PBL) to explore conceptual online tools and generate attention in the field of MEMS and NEMS. This research describes a teaching style that combines PBL with NEMS and MEMS online courses for undergraduate students. This research work delves into the principles and ideas of Micro- and Nano-electronic models. Teaching styles develop understanding, skills, and values relative to the subject. The basics of MOSFETs, cantilever beams, biosensors, comb drive, piezoelectric devices, etc. are also examined clearly through assignments. The online platform is designed to develop creative concepts and model devices for future applications. Using the PBL technique, this research work fosters both academics and students' self-learning, resulting in more sophisticated studies on subjects such as NEMS, MEMS, and Bio-MEMS. This work displays its text description as well as numerical simulations. In a controlled experiment, two sets of pre- and post-evaluation analyses have been conducted to look at the impact of PBL utilizing numerical simulation tools on fundamental theory learning. The analytical assessment demonstrates that combining numerical simulation with PBL results in more efficient understanding of fundamental MEMS and NEMS ideas. It will be a potential teaching modality for the development of online courses in this area. © 2022 IEEE.

Rapid SARS-CoV-2 S-protein Detection using Nanostructured Electrochemical Biosensor

We have developed a new type of testing strategy based on the electrochemical biosensing aspect for rapid and portable detection of SARS-CoV-2. The detection platform is based on a highly conductive matrix (fabricated polystyrene/polyaniline-Au nanocomposite) enabling immobilization of representative receptor elements (antibodies) that are specific to the target, i.e., SARS-CoV-2 spike (S)-protein. The concept of a detection system is to translate specific covalent interaction between antibodies and its corresponding binding viral S-protein, into a measurable, concentration-dependent electrochemical signal. The biosensor is able to monitor the electrochemical response in PBS, without using hazardous [Fe(CN)]63-/4- redox couple. By creating an electrochemical readout (CV, EIS, and DPV), data enables qualitative and quantitative analysis. Additionally, it exploits outstanding conductivity and biocompatibility, thus resulting in high analytical sensitivity and a low detection limit of 15.6μ g/mL, which is within the physiologically relevant concentration range. Thus, the proposed feasible design of the biosensor platform represents an excellent starting point for practical and low-cost testing of asymptomatic patients or people before symptom onset. © 2022 IEEE.

A Novel Snore Detection and Suppression Method for a Flexible Patch With MEMS Microphone and Accelerometer

Sleep apnea impacts more and more people all over the world, and obstructive sleep apnea of which is the most frequent. Hence, research on snoring detection and related suppression methods is extremely urgent. In this article, a novel low-cost flexible patch with MEMS microphone and accelerometer is developed to detect snore event and sleeping posture, and a small vibration motor embedded in the patch is designed to suppress snoring. Theoretical analyses of short-time energy, piecewise average filtering (PAF), and Mel-frequency cepstral coefficients (MFCCs) processing are described in detail, and the improved MFCCs are put forward and used as the input of the convolutional neural network (CNN). Furthermore, the snore recognition method based on the combination of similarity analysis and CNN analysis is presented, followed by the snoring suppression method. Experimental results demonstrate that the main features of the sound signals can be extracted effectively by PAF and MFCCs processing, and the data compression ratio is about 99.41%. Besides, the locations of the eigenvectors can be found accurately based on short-time energy analysis. The numbers of high similarity of snoring signals within 30 s are larger than 3, while those of non-snoring signals are often less than 3. If the preliminary screening with similarity analysis is passed, CNN analysis will be conducted to judge whether there are snoring events. The accuracy of snore recognition with CNN analysis is calculated to be as high as 99.25%. Finally, the average snoring time measured by the smart patch with snoring suppression is reduced to 15 from 135 min, which indicates that the proposed snore recognition and suppression methods are effective.

Smart Online Oxygen Supply Management though Internet of Things (IoT)

We are surrounded by oxygen in the air we We cannot even exist without the ability to breathe. The need for oxygen has increased during the COVID19 pandemic, and although there is enough oxygen in our country, the main issue is getting it to hospitals or those in need on time. This is simply due to a significant communication gap between suppliers and hospitals, so we plan to implement an idea that will close this gap using real-time tracking as we can track the movement of oxygen tankers by gathering the requirements. We are using an ESP32 Wi-Fi module, a MEMS pressure sensor that enables the combination of precise sensors, potential processing, and wireless communication, such as Wi-Fi, Bluetooth, IFTTT, and MQTT protocols, to implement it successfully. The pressure sensor publishes the value of oxygen remaining from the location to the MQTT broker. © 2022 IEEE.

Electrochemical biosensing based on graphene for detection of the SARS-Co V-2 Nucleocapsid Protein

Monitoring and controlling infection is required in order to prevent the progression of the coronavirus severe acute respiratory syndrome 2(SARS-Co- V-2). To accomplish this goal, the development and implementation of sensitive, quick and accurate diagnostic methods are essential. Electrochemical sensors have exposed large application possibilities in biological detection due to the advantages of high sensitivity, short time-consuming and specificity. Here, we report the improvement of a sensitive electrochemical sensor capable of detecting the presence of the SARS-CoV-2 virus using graphene-modified interdigitated working electrodes functionalized with antibodies targeting the SARS-CoV-2 nucleocapsid protein (N protein). © 2022 IEEE.

InGaAs based gratings for UV-VIS spectrometer in prospective mRNA vaccine research.

During the outbreak of the COVID-19 illness, mRNA (messenger RNA) injections proved to be effective vaccination. Among the presently available analytical techniques, UV/VIS spectrophotometry is a trustworthy and practical instrument that may provide information on the chemical components of the vaccine at the molecular level. In this paper, we will present a one-dimensional grating of InGaAs as a prospect grating structure for UV-VIS spectrometer that can be used for mRNA vaccine development. The main parameters and the wavelength region used in mRNA vaccine development lies in the range of 200 nm to 700 nm (UV-VIS Range). The incorporation of new materials that are excellent for cutting-edge semiconductor industry procedures for MEMS manufacture, as well as new optimal parameters, will improve the grating and spectrometer's performance which will enhance the mRNA vaccine development and manufacturing workflows enabled by UV-VIS spectroscopy. Hence we evaluated the feasibility of the materials, Si (Silicon), GaN (Gallium Nitride), InGaAs (Indium Gallium Arsenide) and InP (Indium Phosphide) as a grating material. Reflection spectrum of the proposed structure shows 48% increase compared to the grating made up of Silicon. In order to model wave propagation in one grating unit cell, electromagnetic waves frequency domain interface is used. The periodic constraints of floquet periodicity are used for simulation at both faces of the unit cell. The reflectance of grating with each material as functions of the angle of incidence was plotted. Also we evaluated the effect of grating thickness, groove density, spectral resolution and efficiency over different materials namely Si, GaN, InGaAs and InP. After optimizing geometric parameters, the designed InGaAs based grating achieved a efficiency of 87.45% and can be a reliable prospect for mRNA based vaccine development.

Multilayered Triboelectric Energy Harvester as a Smart Floor Mat

This paper develops a multilayered triboelectric energy harvester and demonstrates its application as a smart floor mat. Triboelectrification is the process in which contact and separation between two triboelectric electrode surfaces result in the generation of opposite charges on them. Due to the tendency of conductive materials to attain charge equilibrium, the electrons flow from the ground to the conductor or vice versa to make it neutral. As a result, an alternating current (AC) flows in the external circuit as the materials contact and separate. In this work, we fabricated an array of triboelectric nanogenerators (TENG) by connecting eight zigzag-shaped multilayered TENGs (each containing three units) in series to realize a smart floor mat. The TENG array was sandwiched between two wooden slabs and was placed in front of the library entrance to control the occupancy by tracking the number of people entering/leaving. This smart floor mat generated a maximum output power of 119.7 μW, which lit up to 40 light-emitting diodes (2mA current with 10μF capacitance) when the mat was compressed and released periodically. The device will have potential applications in tracking the number of people entering/leaving a facility. In this Covid-19 era, the control of occupancy rate becomes more crucial in an indoor setting such as in libraries, shopping malls, etc. This study provides a simple, straightforward, and low-cost solution to achieving the control measure. In addition, the traditional occupancy tracking systems based on cameras, processors, and sensors are expensive compared to our low-cost and energy-efficient smart floor mat. Hence, our design has the potential to provide a promising alternative to the existing solutions. © 2022 IEEE.

DUV-LED packaging using high density TSV in silicon cavity and laser-glass-frit-bonded UV transmitting glass cap

This paper reports an improved deep ultraviolet LED (DUV-LED) packaging based on Si Micro-Electro-Mechanical Systems (MEMS) process technology. The Si package (Si-PKG) consists of a cavity formed by Si crystalline anisotropic wet etching and through-silicon vias (TSVs) filled with electroplated Cu. The Si-PKG is hermetically sealed by laser local heating of screen-printed glass frit. This technology allows for the use of a DUV-transparent glass substrate, which has an unmatched coefficient of thermal expansion (CTE). Using a high-density array of TSV capped with AuSn solder bumps, the cooling performance of the DUV-LED has been greatly improved. And the contribution by the Si (111) side reflection of Si-PKG to the total light output was confirmed 13 %. As a result, an optical output of 114 % (50 mW) and a volumetric light power density of 380 % (14 mW/mm3) were recorded compared with the conventional AlN-packaged device. The developed compact low-cost Si-PKG is promising for wider applications of the DUV-LED including the disinfection of the new coronaviruses. © 2022 Elsevier B.V.

Wearable Piezoelectric BioMEMS-based Sensor for SARS-CoV-2 (COVID-19) Virus Droplets Detection

Viral diagnostic is essential to the fields of medicine and bio-nanotechnology, but such analyses can present some complex analytical challenges. While molecular methods that are mostly used in clinical laboratories, for instance, reverse transcription-polymerase chain reaction (RT-PCR) and antigens tests require long acquisition times, and often provides unreliable results for COVID-19 virus detection, the piezo-based sensors coupled with MEMS have demonstrated a significant role in robust viral detection. In this work, we have designed and simulated a piezoelectric MEMS-based biosensor integrated into a wearable face mask for early detection of the SARS-CoV-2 virus droplets. We systematically investigated the influence of virus droplets in changing the applied stress on the cantilever receptor pit with change in mass when viruses (pathogens) from airborne coughing droplets-nuclei binds with coated antibodies on the sensor's cantilever layer with receptor pit thereby generating electric potential. Additionally, Bio-MEMS sensor results have manifested that it has the ability to detect a single size particle of 1 virion with a diameter ≥100 nm and mass of 1fg in a single cough containing droplet nuclei of radius 0.05μm in a less amount of time. Additionally, we empirically set electrical potential as thresholds parameter for our wearable biosensor embedded in the face mask for public monitoring to detect contagious virus particle droplets. Furthermore, this study presented the prospective use of MEMS-based sensing method to identify and detect other biological (bacteria and toxins) analytes. © 2021 IEEE.

Multimodal wearable platform for remote monitoring of breathing patterns, cough events and blood oxygen level

Wearable technologies are essential for telehealth services and for reducing the load on the healthcare systems. The wearables enable individuals to personalize health monitoring out of hospitals and allow physicians to remotely assess the health status of individuals and track the recovery process. Here, we developed a multimodal wearable device to record breathing patterns and cough events with a low noise, wide dynamic range microelectromechanical accelerometer. In addition, the wearable device included a high-sensitivity pulse oximeter and heart rate to record blood oxygen saturation levels. The device recorded cough vibrations, oxygen saturation level and a respiratory profile that can be used for evaluation of the respiratory system. The device was tested on healthy volunteers and a subject with COVID-19 during quarantine. © COPYRIGHT SPIE. Downloading of the is permitted for personal use only.

Brighten Buildings Naturally to Boost Immunity and Fight Covid19 Using Optimized MEMS-Based Daylighting Systems

Everyone knows that a strong immune system is one of the keys to fighting Covid19. Washing our hands regularly, practicing social distancing and eating nutritious foods are also important behaviors that help us to prevent the infection. However, during the Covid19 period, sitting down for long periods of time without exposing to sun makes us more susceptible to illness and disease. Furthermore, most of people suffer from stress and thus tend to have weakened immune cells that lack the ability to effectively fight viruses. So, they become more prone to viral infections. In this paper, we propose a solution to brighten buildings, hospitals and schools using optimized MEMS-based daylighting systems in order to repair and strengthen the immunity against viruses like Covid19 and thus saving lives.

Advancements of Lab on Chip in Reducing Human Intervention: A Study

The tremendous advancements in nanotechnology have given life to the technology called Lab-on-Chip (LoC). The Nanoscale impression on semiconductors and the metals are achieved by the Lithography processes. Many of the experiments and analysis which are to be done in the laboratory have been done on this miniaturized module. The LoC technology helps to perform many laboratory functions on a single few centimeters chip size. This helps achieve high-throughput screening and automation. LoC technology requires a very less sample in drops for the analysis of the sample provided and also helps in cost effectiveness and speed response. It has great control over the concentration of samples as well as interactions to reduce the huge chemical waste. LoC through mass production aids to the development of highly compact design of systems. This paper overviews the development in the field of LoC. © 2021 IEEE.

Covid-19 Patient Breath Monitoring and Assessment with Mems Accelerometer-Based Daq-a Machine Learning Approach

The coronavirus-2 infection, which emerged in 2019, is a severe illness that can cause acute respiratory failure and death. The effects of the coronavirus-2 disease on the respiratory system have been studied. This paper aims to develop a wearable device that can provide reliable and cost-effective respiratory monitoring. The hardware has been installed on COVID-19 infected individuals and healthy individuals. The study's goal is to find abnormalities in the data sets that can be used to estimate the respiration rate. © 2022, International Journal of Special Education. All rights reserved.