612 research outputs found

    Novel Smart N95 Filtering Facepiece Respirator with Real-time Adaptive Fit Functionality and Wireless Humidity Monitoring for Enhanced Wearable Comfort

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    The widespread emergence of the COVID-19 pandemic has transformed our lifestyle, and facial respirators have become an essential part of daily life. Nevertheless, the current respirators possess several limitations such as poor respirator fit because they are incapable of covering diverse human facial sizes and shapes, potentially diminishing the effect of wearing respirators. In addition, the current facial respirators do not inform the user of the air quality within the smart facepiece respirator in case of continuous long-term use. Here, we demonstrate the novel smart N-95 filtering facepiece respirator that incorporates the humidity sensor and pressure sensory feedback-enabled self-fit adjusting functionality for the effective performance of the facial respirator to prevent the transmission of airborne pathogens. The laser-induced graphene (LIG) constitutes the humidity sensor, and the pressure sensor array based on the dielectric elastomeric sponge monitors the respirator contact on the face of the user, providing the sensory information for a closed-loop feedback mechanism. As a result of the self-fit adjusting mode along with elastomeric lining, the fit factor is increased by 3.20 and 5 times at average and maximum respectively. We expect that the experimental proof-of-concept of this work will offer viable solutions to the current commercial respirators to address the limitations.Comment: 20 pages, 5 figures, 1 table, submitted for possible publicatio

    Wellness, Fitness, and Lifestyle Sensing Applications

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    Smartphone-based colorimetric sensor application for measuring biochemical material concentration

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    In this paper, colorimetric analysis for biochemical samples has been realized, by developing an easy-to-use smartphone colorimetric sensing android application that can measure the molar concentration of the biochemical liquid analyte. The designed application can be used for on-site testing and measurement. We examined three different biochemical materials with the application after preparation with five different concentrations and testing in laboratory settings, namely glucose, triglycerides, and urea. Our results showed that for glucose triglycerides, and urea the absorbance and transmittance regression coefficient (R2) for the colorimetric sensing application were 0.9825, and 0.9899; 0.9405 and 0.9502; 0.9431 and 0.8597, respectively. While for the spectrophotometer measurement the (R2) values were 0.9973 @560 nm and 0.9793 @600 nm; 0.952 @620 nm and 0.9364 @410 nm; 0.9948 @570 nm and 0.9827 @530 nm, respectively. The novelty of our study lies in the accurate prediction of multiple biochemical materials concentrations in various lightning effects, reducing the measurement time in an easy-to-use portable environment without the need for internet access, also tackling various issues that arise in the traditional measurements like power consumption, heating, and calibration. The ability to convey multiple tasks, prediction of concentration, measurement of both absorbance and transmittance, with error estimation charts and (R2) values reporting within the colorimetric sensing application as far as our knowledge there has not been any application that can provide all the capabilities of our application

    Wearable devices and IoT applications for symptom detection, infection tracking, and diffusion containment of the COVID-19 pandemic: a survey

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    Until a safe and effective vaccine to fight the SARS-CoV-2 virus is developed and available for the global population, preventive measures, such as wearable tracking and monitoring systems supported by Internet of Things (IoT) infrastructures, are valuable tools for containing the pandemic. In this review paper we analyze innovative wearable systems for limiting the virus spread, early detection of the first symptoms of the coronavirus disease COVID-19 infection, and remote monitoring of the health conditions of infected patients during the quarantine. The attention is focused on systems allowing quick user screening through ready-to-use hardware and software components. Such sensor-based systems monitor the principal vital signs, detect symptoms related to COVID-19 early, and alert patients and medical staff. Novel wearable devices for complying with social distancing rules and limiting interpersonal contagion (such as smart masks) are investigated and analyzed. In addition, an overview of implantable devices for monitoring the effects of COVID-19 on the cardiovascular system is presented. Then we report an overview of tracing strategies and technologies for containing the COVID-19 pandemic based on IoT technologies, wearable devices, and cloud computing. In detail, we demonstrate the potential of radio frequency based signal technology, including Bluetooth Low Energy (BLE), Wi-Fi, and radio frequency identification (RFID), often combined with Apps and cloud technology. Finally, critical analysis and comparisons of the different discussed solutions are presented, highlighting their potential and providing new insights for developing innovative tools for facing future pandemics

    Error Prevention in Sensors and Sensor Systems

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    Achievements in all fields of engineering and fabrication methods have led towards optimization and integration of multiple sensing devices into a concise system. These advances have caused significant innovation in various commercial, industrial, and research efforts. Integrations of subsystems have important applications for sensor systems in particular. The need for reporting and real time awareness of a device’s condition and surroundings have led to sensor systems being implemented in a wide variety of fields. From environmental sensors for agriculture, to object characterization and biomedical sensing, the application for sensor systems has impacted all modern facets of innovation. With these innovations, however, additional sources of errors can occur, that can cause new but exciting challenges for such integrated devices. Such challenges range from error correction and accuracy to power optimization. Researchers have invested significant time and effort to improve the applicability and accuracy of sensors and sensor systems. Efforts to reduce inherent and external noise of sensors can range from hardware to software solutions, focusing on signal processing and exploiting the integration of multiple signals and/or sensor types. My research work throughout my career has been focused on deployable and integrated sensor systems. Their integration not only in hardware and components but also in software, machine learning, pattern recognition, and overall signal processing algorithms to aid in error correction and noise tailoring in all their hardware and software components

    DEVELOPMENT OF PIEZOELECTRIC SENSORS AND METHODOLOGY FOR NONINVASIVE SIMULTANEOUS DETECTION OF MULTIPLE VITAL SIGNS

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    The activity of piezoelectric material linked the applied electric field with the strain generated that can be translated into geometrical variations. Flexible steel substrate exhibits fascinating mechanical properties which enable their integration into the emerging field of flexible microelectronics. This work presents an extended technique based on capacitance-voltage dependency to extract the geometrical variations in thin-film piezoelectric materials deposited on a flexible steel. A 50 μm flexible steel sheet has been sandwiched by two PZT film layers, each of 2.4 μm in thickness deposited by sputtering. An aluminum layer of 370 nm has been deposited above each PZT layer to form the electrical contact. The steel sheet represents the common electrode for both PZT structures. Gamry references 3000 analyzers were used to collect the capacitance-voltage measurements then estimating the piezoelectric charge constant. Experimental work has been validated by implementing the same method on a bulk piezoelectric film. Results have shown that the measured capacitance varies by 1% due to dielectric constant voltage dependency. On the other hand, 99% of capacitance variations depend on the change in physical dimensions of the sample via the piezoelectric effect. Further to that, this thesis explores the utilization of piezoelectric-based sensors to collect a corresponding representative signal from the chest surface. The subject typically needs to hold his or her breath to eliminate the respiration effect. This work further contributes to the extraction of the corresponding representative vital signs directly from the measured respiration signal. The contraction and expansion of the heart muscles, as well as the respiration activities, will induce a mechanical vibration across the chest wall. This vibration can be converted into an electrical output voltage via piezoelectric sensors. During breathing, the measured voltage signal is composed of the cardiac cycle activities modulated along with the respiratory cycle activity. The proposed technique employs the principles of piezoelectric and signal-processing methods to extract the corresponding signal of cardiac cycle activities from a breathing signal measured in real-time. All the results were validated step by step by a conventional apparatus, with good agreement observed

    Connected Car: technologies, issues, future trends

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    The connected car -a vehicle capable of accessing to the Internet, of communicating with smart devices as well as other cars and road infrastructures, and of collecting real-time data from multiple sources- is likely to play a fundamental role in the foreseeable Internet Of Things. In a context ruled by very strong competitive forces, a significant amount of car manufacturers and software and hardware developers have already embraced the challenge of providing innovative solutions for new generation vehicles. Today’s cars are asked to relieve drivers from the most stressful operations needed for driving, providing them with interesting and updated entertainment functions. In the meantime, they have to comply to the increasingly stringent standards about safety and reliability. The aim of this paper is to provide an overview of the possibilities offered by connected functionalities on cars and the associated technological issues and problems, as well as to enumerate the currently available hardware and software solutions and their main features

    Architecture and Applications of IoT Devices in Socially Relevant Fields

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    Number of IoT enabled devices are being tried and introduced every year and there is a healthy competition among researched and businesses to capitalize the space created by IoT, as these devices have a great market potential. Depending on the type of task involved and sensitive nature of data that the device handles, various IoT architectures, communication protocols and components are chosen and their performance is evaluated. This paper reviews such IoT enabled devices based on their architecture, communication protocols and functions in few key socially relevant fields like health care, farming, firefighting, women/individual safety/call for help/harm alert, home surveillance and mapping as these fields involve majority of the general public. It can be seen, to one's amazement, that already significant number of devices are being reported on these fields and their performance is promising. This paper also outlines the challenges involved in each of these fields that require solutions to make these devices reliableComment: 1
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