With the recent SARS-CoV-2 outbreak, the importance of rapid and direct detection of respiratory disease viruses has been well recognized. The detection of these viruses with novel technologies is vital in timely prevention and treatment strategies for epidemics and pandemics. Respiratory viruses can be detected from saliva, swab samples, nasal fluid, and blood, and collected samples can be analyzed by various techniques. Conventional methods for virus detection are based on techniques relying on cell culture, antigen-antibody interactions, and nucleic acids. However, these methods require trained personnel as well as expensive equipment. Microfluidic technologies, on the other hand, are one of the most accurate and specific methods to directly detect respiratory tract viruses. During viral infections, the production of detectable amounts of relevant antibodies takes a few days to weeks, hampering the aim of prevention. Alternatively, nucleic acid–based methods can directly detect the virus-specific RNA or DNA region, even before the immune response. There are numerous methods to detect respiratory viruses, but direct detection techniques have higher specificity and sensitivity than other techniques. This review aims to summarize the methods and technologies developed for microfluidic-based direct detection of viruses that cause respiratory infection using different detection techniques. Microfluidics enables the use of minimal sample volumes and thereby leading to a time, cost, and labor effective operation. Microfluidic-based detection technologies provide affordable, portable, rapid, and sensitive analysis of intact virus or virus genetic material, which is very important in pandemic and epidemic events to control outbreaks with an effective diagnosis.
Sleep apnea is a disease that occurs during sleep, which affects the daily life of patients due to the obstruction of the upper respiratory tract and decreases oxygen level in blood and it may even lead to patient death in the later stage. Monitoring the patients regularly has absolute importance to prevent patient disorders caused by sleep apnea. Wearable sensor technologies and patient tracking systems provide diagnosis, treatment, and monitoring of patients, and procure better health services in medical fields. In addition to decreasing the workload of health institutions, remote patient monitoring systems can serve continuous monitoring and determine variable symptoms of the patients. In this paper, we propose a patient monitoring system, which will be used for diagnosis and monitoring of sleep apnea by tracking the respiratory rate of patients with wearable sensor technology. The respiratory rate is detected using either an accelerometer sensor to be placed on the patients' abdomen or a temperature sensor to be placed on their noses. The proposed system offers an increase in the versatility of patient monitoring systems and offers an alternative new technology in sleep apnea diagnosis.
Information technologies give patients the opportunity to communicate with medical professionals remotely. Telemedicine uses these technologies to provide advanced healthcare and medical services. We present a medical online consultation application based on Web Real-Time Communications (WebRTC) technology enabling chat, audio, and video calls. Communication architecture and protocols of the application are explained in detail. Additionally, the user interface of the application is shown via performed calls. The application is tested and evaluated on different network connections (3G, 4G, local, and DSL) and different browsers and mobile operating systems (Android, Chrome, Firefox, Internet Explorer, iOS, Opera, Safari). During calls, communication quality parameters such as round-trip time (RTT) and packet loss, obtained via the WebRTC application programming interface, are analyzed. 3G, 4G, and local connections show low packet losses ( < 1%). Packet losses are high ( > 1%) in Android, Chrome, iOS, Opera, and Safari for DSL connection, but RTT values are low ( < 100 ms) in all different conditions excluding iOS. In the presented application, RTT and packet loss remain lower than 100 ms and 1%, respectively, in various scenarios, indicating good communication quality. RTT and packet loss are related to total time and hang time parameters, which describe the necessary time to establish and to end a call. It is shown that communication quality of the application can simply be measured by analyzing the total time parameter. This enables predictable information for communication quality forWebRTC-based applications without continuously monitoring RTT and packet loss for the first time.
The COVID-19 pandemic has posed significant challenges to existing healthcare systems around the world. The urgent need for the development of diagnostic and therapeutic strategies for COVID-19 has boomed the demand for new technologies that can improve current healthcare approaches, moving towards more advanced, digitalized, personalized, and patient-oriented systems. Microfluidic-based technologies involve the miniaturization of large-scale devices and laboratory-based procedures, enabling complex chemical and biological operations that are conventionally performed at the macro-scale to be carried out on the microscale or less. The advantages microfluidic systems offer such as rapid, low-cost, accurate, and on-site solutions make these tools extremely useful and effective in the fight against COVID-19. In particular, microfluidic-assisted systems are of great interest in different COVID-19-related domains, varying from direct and indirect detection of COVID-19 infections to drug and vaccine discovery and their targeted delivery. Here, we review recent advances in the use of microfluidic platforms to diagnose, treat or prevent COVID-19. We start by summarizing recent microfluidic-based diagnostic solutions applicable to COVID-19. We then highlight the key roles microfluidics play in developing COVID-19 vaccines and testing how vaccine candidates perform, with a focus on RNA-delivery technologies and nano-carriers. Next, microfluidic-based efforts devoted to assessing the efficacy of potential COVID-19 drugs, either repurposed or new, and their targeted delivery to infected sites are summarized. We conclude by providing future perspectives and research directions that are critical to effectively prevent or respond to future pandemics.
Chronic kidney disease (CKD) is a high-cost disease that affects approximately one in ten people globally, progresses rapidly, results in kidney failure or dialysis, and triggers other diseases. Although clinically used serum creatinine tests are used to evaluate kidney functions, these tests are not suitable for frequent and regular control at-home settings that obstruct the regular monitoring of kidney functions, improving CKD management with early intervention. This study introduced a new electromechanical lab-on-a-chip platform for point-of-care detection of serum creatinine levels using colorimetric enzyme-linked immunosorbent assay (ELISA). The platform was composed of a chip containing microreservoirs, a stirring bar coated with creatinine-specific antibodies, and a phone to detect color generated via ELISA protocols to evaluate creatinine levels. An electromechanical system was used to move the stirring bar to different microreservoirs and stir it inside them to capture and detect serum creatinine in the sample. The presented platform allowed automated analysis of creatinine in ∼50 min down to ∼1 and ∼2 mg/dL in phosphate-buffered saline (PBS) and fetal bovine serum (FBS), respectively. Phone camera measurements in hue, saturation, value (HSV) space showed sensitive analysis compared to a benchtop spectrophotometer that could allow low-cost analysis at point-of-care.
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