Lab-on-Mask for Remote Respiratory Monitoring

Protective face mask: an effective weapon against SARS-CoV-2 with controlled environmental pollution

Masks are face coverings that give protection from infectious agents, airborne pathogens, bacteria, viruses, surgical fog, dust, and other chemical hazards by acting as a barrier between the wearer and the environment. In the COVID-19 pandemic, this major personal protective equipment's became essential part of our daily life. The aim of this review is to analyze and discuss the different types of masks with their pros and cons, manufacturing procedures, evaluation criteria, and application with some of the sterilization process for reuse and smart mask. The review used a thorough examination of the literature to analyze the preventive effects of surgical, N95, smart mask, and potential environmental damage from those masks. Several studies and evidence were also examined to understand the efficiency of different mask on different environment. N95 respirators are capable of filtering out non-oil-based 95% air-born particles, and surgical masks act as a protective barrier between the wearer and the environment. The application of spoon bond and melt blown techniques in the fabrication process of those masks improves their protective nature and makes them lightweight and comfortable. But the high demand and low supply forced users to reuse and extend their use after sterilizations, even though those masks are recommended to be used once. Universal masking in the SARS-COV-2 pandemic increased the chance of environmental pollution, so the application of smart masks became essential because of their high protection power and self-sterilizing and reusing capabilities.

Tracing the Flu Symptom Progression via a Smart Face Mask

Respiration and body temperature are largely influenced by the highly contagious influenza virus, which poses persistent global public health challenges. Here, we present a wireless all-in-one sensory face mask (WISE mask) made of ultrasensitive fibrous temperature sensors. The WISE mask shows exceptional thermosensitivity, excellent breathability, and wearing comfort. It offers highly sensitive body temperature monitoring and respiratory detection capabilities. Capitalizing on the advances in the Internet of Things and artificial intelligence, the WISE mask is further demonstrated by customized flexible circuitry, deep learning algorithms, and a user-friendly interface to continuously recognize the abnormalities of both the respiration and body temperature. The WISE mask represents a compelling approach to tracing flu symptom progression in a cost-effective and convenient manner, serving as a powerful solution for personalized health monitoring and point-of-care systems in the face of ongoing influenza-related public health concerns.

Microfluidic Wearable Devices for Sports Applications

This study aimed to systematically review the application and research progress of flexible microfluidic wearable devices in the field of sports. The research team thoroughly investigated the use of life signal-monitoring technology for flexible wearable devices in the domain of sports. In addition, the classification of applications, the current status, and the developmental trends of similar products and equipment were evaluated. Scholars expect the provision of valuable references and guidance for related research and the development of the sports industry. The use of microfluidic detection for collecting biomarkers can mitigate the impact of sweat on movements that are common in sports and can also address the issue of discomfort after prolonged use. Flexible wearable gadgets are normally utilized to monitor athletic performance, rehabilitation, and training. Nevertheless, the research and development of such devices is limited, mostly catering to professional athletes. Devices for those who are inexperienced in sports and disabled populations are lacking. Conclusions: Upgrading microfluidic chip technology can lead to accurate and safe sports monitoring. Moreover, the development of multi-functional and multi-site devices can provide technical support to athletes during their training and competitions while also fostering technological innovation in the field of sports science.

Wearable Graphene-based smart face mask for Real-Time human respiration monitoring

After the pandemic of SARS-CoV-2, the use of face-masks is considered the most effective way to prevent the spread of virus-containing respiratory fluid. As the virus targets the lungs directly, causing shortness of breath, continuous respiratory monitoring is crucial for evaluating health status. Therefore, the need for a smart face mask (SFM) capable of wirelessly monitoring human respiration in real-time has gained enormous attention. However, some challenges in developing these devices should be solved to make practical use of them possible. One key issue is to design a wearable SFM that is biocompatible and has fast responsivity for non-invasive and real-time tracking of respiration signals. Herein, we present a cost-effective and straightforward solution to produce innovative SFMs by depositing graphene-based coatings over commercial surgical masks. In particular, graphene nanoplatelets (GNPs) are integrated into a polycaprolactone (PCL) polymeric matrix. The resulting SFMs are characterized morphologically, and their electrical, electromechanical, and sensing properties are fully assessed. The proposed SFM exhibits remarkable durability (greater than1000 cycles) and excellent fast response time (∼42 ms), providing simultaneously normal and abnormal breath signals with clear differentiation. Finally, a developed mobile application monitors the mask wearer's breathing pattern wirelessly and provides alerts without compromising user-friendliness and comfort.

Moving toward smart biomedical sensing

The development of novel biomedical sensors as highly promising devices/tools in early diagnosis and therapy monitoring of many diseases and disorders has recently witnessed unprecedented growth; more and faster than ever. Nonetheless, on the eve of Industry 5.0 and by learning from defects of current sensors in smart diagnostics of pandemics, there is still a long way to go to achieve the ideal biomedical sensors capable of meeting the growing needs and expectations for smart biomedical/diagnostic sensing through eHealth systems. Herein, an overview is provided to highlight the importance and necessity of an inevitable transition in the era of digital health/Healthcare 4.0 towards smart biomedical/diagnostic sensing and how to approach it via new digital technologies including Internet of Things (IoT), artificial intelligence, IoT gateways (smartphones, readers), etc. This review will bring together the different types of smartphone/reader-based biomedical sensors, which have been employing for a wide variety of optical/electrical/electrochemical biosensing applications and paving the way for future eHealth diagnostic devices by moving towards smart biomedical sensing. Here, alongside highlighting the characteristics/criteria that should be met by the developed sensors towards smart biomedical sensing, the challenging issues ahead are delineated along with a comprehensive outlook on this extremely necessary field.

Smart Mask as Wearable for Post-Pandemic Personal Healthcare

A mask serves as a simple external barrier that protects humans from infectious particles from poor air conditions in the surrounding environment. As an important personal protective equipment (PPE) to protect our respiratory system, masks are able not only to filter pathogens and dust particles but also to sense, reflect or even respond to environmental conditions. This smartness is of particular interest among academia and industries due to its potential in disease detection, health monitoring and caring aspects. In this review, we provide an overlook of the current air filtration strategies used in masks, from structural designs to integrated functional modules that empower the mask's ability to sense and transfer physiological or environmental information to become smart. Specifically, we discussed recent developments in masks designed to detect macroscopic physiological signals from the wearer and mask-based disease diagnoses, such as COVID-19. Further, we propose the concept of next-generation smart masks and the requirements from material selection and function design perspectives that enable masks to interact and play crucial roles in health-caring wearables.

A Sensor-Integrated Face Mask Using Au@SnO2 Nanoparticle Modified Fibers and Augmented Reality Technology

In this work, we develop a wireless sensor-integrated face mask using Au@SnO₂ nanoparticle-modified conductive fibers based on augmented reality (AR) technology. AR technology enables the overlay of real objects and environments with virtual 3D objects and allows virtual interactions with real objects to create desired meanings. With the help of the AR system, the size of the mask could be precisely estimated and then manufactured using 3D printing technology. The body temperature sensor and respiratory sensor were integrated into the mask so that vital parameters of the human body could be continuously monitored without removing the personal protective equipment. Furthermore, the outer part of the mask consists of conductive fabric modified with Au@SnO₂ core-shell nanoparticle additives, which enhanced the filtration efficiency of airborne aerosols. A significant improvement in the filtration efficiency of particulate matter 2.5 was observed after applying an external voltage to the conductive textiles. A smartwatch with a heart rate sensor was paired with the mask to display sensor data on the mask through wireless transmission. Therefore, this sensor-integrated mask system with AR technology provides the first line of defense to combat global threats from pathogens and air pollutants.

Wide-Bandwidth Nanocomposite-Sensor Integrated Smart Mask for Tracking Multiphase Respiratory Activities

Wearing masks has been a recommended protective measure due to the risks of coronavirus disease 2019 (COVID-19) even in its coming endemic phase. Therefore, deploying a "smart mask" to monitor human physiological signals is highly beneficial for personal and public health. This work presents a smart mask integrating an ultrathin nanocomposite sponge structure-based soundwave sensor (≈400 µm), which allows the high sensitivity in a wide-bandwidth dynamic pressure range, i.e., capable of detecting various respiratory sounds of breathing, speaking, and coughing. Thirty-one subjects test the smart mask in recording their respiratory activities. Machine/deep learning methods, i.e., support vector machine and convolutional neural networks, are used to recognize these activities, which show average macro-recalls of ≈95% in both individual and generalized models. With rich high-frequency (≈4000 Hz) information recorded, the two-/tri-phase coughs can be mapped while speaking words can be identified, demonstrating that the smart mask can be applicable as a daily wearable Internet of Things (IoT) device for respiratory disease identification, voice interaction tool, etc. in the future. This work bridges the technological gap between ultra-lightweight but high-frequency response sensor material fabrication, signal transduction and processing, and machining/deep learning to demonstrate a wearable device for potential applications in continual health monitoring in daily life.

Biodegradable Smart Face Masks for Machine Learning-Assisted Chronic Respiratory Disease Diagnosis

Utilizing smart face masks to monitor and analyze respiratory signals is a convenient and effective method to give an early warning for chronic respiratory diseases. In this work, a smart face mask is proposed with an air-permeable and biodegradable self-powered breath sensor as the key component. This smart face mask is easily fabricated, comfortable to use, eco-friendly, and has sensitive and stable output performances in real wearable conditions. To verify the practicability, we use smart face masks to record respiratory signals of patients with chronic respiratory diseases when the patients do not have obvious symptoms. With the assistance of the machine learning algorithm of the bagged decision tree, the accuracy for distinguishing the healthy group and three groups of chronic respiratory diseases (asthma, bronchitis, and chronic obstructive pulmonary disease) is up to 95.5%. These results indicate that the strategy of this work is feasible and may promote the development of wearable health monitoring systems.

Silver Nanoparticle-Decorated Multiwalled Carbon Nanotube Ink for Advanced Wearable Devices

Silver nanoparticles of average size 12-13 nm were successfully decorated on the surface of multiwalled carbon nanotubes (MWCNTs) through a scalable wet chemical method without altering the structure of the MWCNTs. Employing this Ag@MWCNT, a multifunctional room-temperature curable conductive ink was developed, with PEDOT:PSS as the conductive binder. Screen printing of the ink could yield conductive planar traces with a 9.5 μm thickness and a conductivity of 28.99 S/cm, minimal surface roughness, and good adhesion on Mylar and Kapton. The versatility of the ink for developing functional elements for printed electronics was demonstrated by fabricating prototypes of a wearable strain sensor, a smart glove, a wearable heater, and a wearable breath sensor. The printed strain sensor exhibited a massive sensing range for wearable applications, including an impressive 1332% normalized resistance change under a maximum stretchability of 23% with superior cyclic stability up to 10 000 cycles. The sensor also exhibited an impeccable gauge factor of 142 for a 5% strain (59 for 23%). Furthermore, the sensor was integrated into a smart glove that could flawlessly replicate a human finger's gestures with a minimal response time of 225-370 ms. Piezoresistive vibration sensors were also fabricated by printing the ink on Mylar, which was employed to fabricate a smart mask and a smart wearable patch to monitor variations in human respiratory and pulmonary cycles. Finally, an energy-efficient flexible heater was fabricated using the developed ink. The heater could generate a uniform temperature distribution of 130 °C at the expense of only 393 mW/cm² and require a minimum response time of 20 s. Thus, the unique formulation of Ag@MWCNT ink proved suitable for versatile devices for future wearable applications.

Smart face shield for the monitoring of COVID-19 physiological parameters: Personal protective equipment (PPE) for health-care workers (HCW’s) and COVID-19 patients

The COVID-19 pandemic has triggered instabilities in various aspects of daily life. This includes economic, social, financial, and health crisis. In addition, the COVID-19 pandemic with the evolution of different virus strains such as delta and omicron has led to frequent global lockdowns. These lockdowns have caused disruption of trade activities that in turn have led to the shortage of medical supplies, especially personal protective equipment’s (PPE’s). Health-care workers (HCW’s) have been at the forefront of the fight against this pandemic and are responsible for saving millions of lives worldwide. However, the PPE’s available to HCW’s in the form of face shields and face masks only provide face and eye protection without encapsulating the ability to continuously monitor vital COVID-19 parameters including body temperature, heart rate, and SpO2. Hence, in this study, we propose the design and utilization of a PPE in the form of smart face shield. The device has been integrated with the MAX30102 sensor for measuring the heart rate and oxygen saturation (SpO2) and the DS18B20 body temperature measuring sensor. The readings of these sensors are analyzed by a NodeMCU ESP8266 and measurements are displayed on a laptop screen. Also, the Wi-Fi module of NodeMCU ESP8266 enables compatibility with the ThingSpeak mobile application and permits HCW’s and patients recovering from COVID-19 to keep a track of their physiological parameters. Overall, this PPE has been observed to provide reliable readings and the results indicate that the designed prototype can be used for monitoring COVID-19 essential parameters.

Beyond Pathogen Filtration: Possibility of Smart Masks as Wearable Devices for Personal and Group Health and Safety Management

Face masks are an important way to combat the COVID-19 pandemic. However, the prolonged pandemic has revealed confounding problems with the current face masks, including not only the spread of the disease but also concurrent psychological, social, and economic complications. As face masks have been worn for a long time, people have been interested in expanding the purpose of masks from protection to comfort and health, leading to the release of various “smart” mask products around the world. To envision how the smart masks will be extended, this paper reviewed 25 smart masks (12 from commercial products and 13 from academic prototypes) that emerged after the pandemic. While most smart masks presented in the market focus on resolving problems with user breathing discomfort, which arise from prolonged use, academic prototypes were designed for not only sensing COVID-19 but also general health monitoring aspects. Further, we investigated several specific sensors that can be incorporated into the mask for expanding biophysical features. On a larger scale, we discussed the architecture and possible applications with the help of connected smart masks. Namely, beyond a personal sensing application, a group or community sensing application may share an aggregate version of information with the broader population. In addition, this kind of collaborative sensing will also address the challenges of individual sensing, such as reliability and coverage. Lastly, we identified possible service application fields and further considerations for actual use. Along with daily-life health monitoring, smart masks may function as a general respiratory health tool for sports training, in an emergency room or ambulatory setting, as protection for industry workers and firefighters, and for soldier safety and survivability. For further considerations, we investigated design aspects in terms of sensor reliability and reproducibility, ergonomic design for user acceptance, and privacy-aware data-handling. Overall, we aim to explore new possibilities by examining the latest research, sensor technologies, and application platform perspectives for smart masks as one of the promising wearable devices. By integrating biomarkers of respiration symptoms, a smart mask can be a truly cutting-edge device that expands further knowledge on health monitoring to reach the next level of wearables.

Smart mask – Wearable IoT solution for improved protection and personal health

The use of face masks is an important way to fight the COVID-19 pandemic. In this paper, we envision the Smart Mask, an IoT supported platform and ecosystem aiming to prevent and control the spreading of COVID-19 and other respiratory viruses. The integration of sensing, materials, AI, wireless, IoT, and software will help the gathering of health data and health-related event detection in real time from the user as well as from their environment. In the larger scale, with the help of AI-based analysis for health data it is possible to predict and decrease medical costs with accurate diagnoses and treatment plans, where the comparison of personal data to large-scale public data enables drawing up a personal health trajectory, for example. Key research problems for smart respiratory protective equipment are identified in addition to future research directions. A Smart Mask prototype was developed with accompanying user application, backend and heath AI to study the concept.

A Breathable, Reusable, and Zero-Power Smart Face Mask for Wireless Cough and Mask-Wearing Monitoring

We herein introduce a lightweight and zero-power smart face mask, capable of wirelessly monitoring coughs in real time and identifying proper mask wearing in public places during a pandemic. The smart face mask relies on the compact, battery-free radio frequency (RF) harmonic transponder, which is attached to the inner layer of the mask for detecting its separation from the face. Specifically, the RF transponder composed of miniature antennas and passive frequency multiplier is made of spray-printed silver nanowires (AgNWs) coated with a poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) passivation layer and the recently discovered multiscale porous polystyrene-block-poly(ethylene-ran-butylene)-block-polystyrene (SEBS) substrate. Unlike conventional on-chip or on-board wireless sensors, the SEBS-AgNWs/PEDOT:PSS-based RF transponder is lightweight, stretchable, breathable, and comfortable. In addition, this wireless device has excellent resilience and robustness in long-term and repeated usages (i.e., repeated placement and removal of the soft transponder on the mask). We foresee that this wireless smart face mask, providing simultaneous cough and mask-wearing monitoring, may mitigate virus-transmissive events by tracking the potential contagious person and identifying mask-wearing conditions. Moreover, the ability to wirelessly assess cough frequencies may improve diagnosis accuracy for dealing with several diseases, such as chronic obstructive pulmonary disease.

SARS-CoV-2 in wastewater: From detection to evaluation

SARS-CoV-2 presence in wastewater has been reported in several studies and has received widespread attention among the Wastewater-based epidemiology (WBE) community. Such studies can potentially be used as a proxy for early warning of potential COVID-19 outbreak, or as a mitigation measure for potential virus transmission via contaminated water. In this review, we summarized the latest understanding on the detection, concentration, and evaluation of SARS-CoV-2 in wastewater. Importantly, we discuss factors affecting the quality of wastewater surveillance ranging from temperature, pH, starting concentration, as well as the presence of chemical pollutants. These factors greatly affect the reliability and comparability of studies reported by various communities across the world. Overall, this review provides a broadly encompassing guidance for epidemiological study using wastewater surveillance.

Polylactic acid face masks: Are these the sustainable solutions in times of COVID-19 pandemic?

The global massive consumption of disposable face masks driven by the ongoing COVID-19 pandemic has emerged as a blooming disaster to both the land and marine environment that might last for generations. Growing public concerns have been raised over the management and control of this new form of plastic pollution, and one of the proposed sustainable solution is to use renewable and/or biodegradable resources to develop mask materials in order to minimize their environmental impacts. As a representative biodegradable polymer, polylactic acid (PLA) has been proposed as a promising candidate to produce non-woven face masks instead of those fossil-based polymers. To further explore the feasibility of this alternative mask material, the present work aims to study both the hydrolytic and bio-degradation behaviors of pure PLA-derived 3-ply disposable face masks at ambient temperature. Hydrolytic degradability was investigated at different pH conditions of 2, 7 and 13 with the whole piece of face mask soaked for regular timed intervals up to 8 weeks. Weight loss study showed neutral and acidic conditions had minimal effect on PLA masks, but rapid degradation occurred under basic conditions in the first week with a sharp 25% decrease in weight that slowly tapered off, coupled with solution pH dropping from 13 to 9.6. This trend was supported by mechanical property, bacterial filtration efficiency (BFE) and particulate filtration efficiency (PFE) studies. Masks soaked in basic conditions had their modulus and tensile strength dropped by more than 50% after 8 weeks where the middle layer reached 68% and 90% respectively just after 48 h, and BFE and PFE decreased by 14% and 43% respectively after 4 weeks, which was much more significant than those in neutral and acidic conditions. Base degradation was also supported by nuclear magnetic resonance (NMR) and fourier transform infrared (FTIR), which disclosed that only the middle layer undergo major degradation with random chain scission and cleavage of enol or enolate chain ends, while outer and inner layers were much less affected. Scanning electron microscopy (SEM) attributed this observation to thinner PLA fibers for the middle layer of 3-7 μm diameter, which on average is 3 times smaller. This degradation was further supported by gel permeation chromatography (GPC) which saw an increase in lower molecular weight fragment Mw ~ 800 Da with soaking duration. The biodegradation behavior was studied under OECD 301F specification in sewage sludge environment. Similarly, degradation to the middle meltblown layer was more extensive, where the average weight loss and carbon loss was 25.8% and 25.7% respectively, double that of outer/inner spunbond layer. The results showed that the face masks did not completely disintegrate after 8 weeks, but small solubilized fragments of PLA formed in the biodegradation process can be completely mineralized into carbon dioxide without generation of secondary microplastic pollution in the environment. PLA masks are therefore a slightly greener option to consider in times of a pandemic that the world was caught unprepared; however future research on masks could be geared towards a higher degradability material that fully breaks down into non-harmful components while maintaining durability, filtration and protection properties for users.

Smart Face Mask Based on an Ultrathin Pressure Sensor for Wireless Monitoring of Breath Conditions

A smart face mask that can conveniently monitor breath information is beneficial for maintaining personal health and preventing the spread of diseases. However, some challenges still need to be addressed before such devices can be of practical use. One key challenge is to develop a pressure sensor that is easily triggered by low pressure and has excellent stability as well as electrical and mechanical properties. In this study, a wireless smart face mask is designed by integrating an ultrathin self-powered pressure sensor and a compact readout circuit with a normal face mask. The pressure sensor is the thinnest (totally compressed thickness of ≈5.5 µm) and lightest (total weight of ≈4.5 mg) electrostatic pressure sensor capable of achieving a peak open-circuit voltage of up to ≈10 V when stimulated by airflow, which endows the sensor with the advantage of readout circuit miniaturization and makes the breath-monitoring system portable and wearable. To demonstrate the capabilities of the smart face mask, it is used to wirelessly measure and analyze the various breath conditions of multiple testers.

Smart facemask for wireless CO2 monitoring

The use of facemasks by the general population is recommended worldwide to prevent the spread of SARS-CoV-2. Despite the evidence in favour of facemasks to reduce community transmission, there is also agreement on the potential adverse effects of their prolonged usage, mainly caused by CO2 rebreathing. Herein we report the development of a sensing platform for gaseous CO2 real-time determination inside FFP2 facemasks. The system consists of an opto-chemical sensor combined with a flexible, battery-less, near-field-enabled tag with resolution and limit of detection of 103 and 140 ppm respectively, and sensor lifetime of 8 h, which is comparable with recommended FFP2 facemask usage times. We include a custom smartphone application for wireless powering, data processing, alert management, results displaying and sharing. Through performance tests during daily activity and exercise monitoring, we demonstrate its utility for non-invasive, wearable health assessment and its potential applicability for preclinical research and diagnostics.

Smart Face Mask with an Integrated Heat Flux Sensor for Fast and Remote People's Healthcare Monitoring

The COVID-19 pandemic has highlighted a large amount of challenges to address. To combat the spread of the virus, several safety measures, such as wearing face masks, have been taken. Temperature controls at the entrance of public places to prevent the entry of virus carriers have been shown to be inefficient and inaccurate. This paper presents a smart mask that allows to monitor body temperature and breathing rate. Body temperature is measured by a non-invasive dual-heat-flux system, consisting of four sensors separated from each other with an insulating material. Breathing rate is obtained from the temperature changes within the mask, measured with a thermistor located near the nose. The system communicates by means of long-range (LoRa) backscattering, leading to a reduction in average power consumption. It is designed to establish the relative location of the smart mask from the signal received at two LoRa receivers installed inside and outside an access door. Low-cost LoRa transceivers with WiFi capabilities are used in the prototype to collect information and upload it to a server. Accuracy in body temperature measurements is consistent with measurements made with a thermistor located in the armpit. The system allows checking the correct placement of the mask based on the recorded temperatures and the breathing rate measurements. Besides, episodes of cough can be detected by sudden changes in thermistor temperature.

Remote Monitoring of Patient Respiration with Mask Attachment—A Pragmatic Solution for Medical Facilities

Remote monitoring of vital signs in infectious patients minimizes the risks of viral transmissions to healthcare professionals. Donning face masks could reduce the risk of viral transmissions and is currently practiced in medical facilities. An acoustic-sensing device was attached to face masks to assist medical facilities in remotely monitoring patients’ respiration rate and wheeze occurrence. Usability and functionality studies of the modified face mask were evaluated on 16 healthy participants. Participants were blindfolded throughout the data collection process. Respiratory rates of the participants were evaluated for one minute. The wheeze detection algorithm was assessed by playing 176 wheezes and 176 normal breaths through a foam mannequin. No discomfort was reported from the participants who used the modified mask. The mean error of respiratory rate was found to be 2.0 ± 1.3 breath per minute. The overall accuracy of the wheeze detection algorithm was 91.9%. The microphone sensor that was first designed to be chest-worn has been proven versatile to be adopted as a mask attachment. The current findings support and suggest the use of the proposed mask attachment in medical facilities. This application can be especially helpful in managing a sudden influx of patients in the face of a pandemic.

Conductive Polymer Nanocomposites for Stretchable Electronics: Material Selection, Design, and Applications

Stretchable electronics that can elongate elastically as well as flex are crucial to a wide range of emerging technologies, such as wearable medical devices, electronic skin, and soft robotics. Critical to stretchable electronics is their ability to withstand large mechanical strain without failure while retaining their electrical conduction properties, a feat significantly beyond traditional metals and silicon-based semiconductors. Herein, we present a review of the recent advances in stretchable conductive polymer nanocomposites with exceptional stretchability and electrical properties, which have the potential to transform a wide range of applications, including wearable sensors for biophysical signals, stretchable conductors and electrodes, and deformable energy-harvesting and -storage devices. Critical to achieving these stretching properties are the judicious selection and hybridization of nanomaterials, novel microstructure designs, and facile fabrication processes, which are the focus of this Review. To highlight the potentials of conductive nanocomposites, a summary of some recent important applications is presented, including COVID-19 remote monitoring, connected health, electronic skin for augmented intelligence, and soft robotics. Finally, perspectives on future challenges and new research opportunities are also presented and discussed.

N95 respirator decontamination: a study in reusability

The coronavirus disease 2019 (COVID-19) pandemic had caused a severe depletion of the worldwide supply of N95 respirators. The development of methods to effectively decontaminate N95 respirators while maintaining their integrity is crucial for respirator regeneration and reuse. In this study, we systematically evaluated five respirator decontamination methods using vaporized hydrogen peroxide (VHP) or ultraviolet (254 nm wavelength, UVC) radiation. Through testing the bioburden, filtration, fluid resistance, and fit (shape) of the decontaminated respirators, we found that the decontamination methods using BioQuell VHP, custom VHP container, Steris VHP, and Sterrad VHP effectively inactivated Cardiovirus (3-log10 reduction) and bacteria (6-log10 reduction) without compromising the respirator integrity after 2-15 cycles. Hope UVC system was capable of inactivating Cardiovirus (3-log10 reduction) but exhibited relatively poorer bactericidal activity. These methods are capable of decontaminating 10-1000 respirators per batch with varied decontamination times (10-200 min). Our findings show that N95 respirators treated by the previously mentioned decontamination methods are safe and effective for reuse by industry, laboratories, and hospitals.

Risk assessment of airborne COVID-19 exposure in social settings

The COVID-19 pandemic has led to many countries oscillating between various states of lock-down as they seek to balance keeping the economy and essential services running and minimizing the risk of further transmission. Decisions are made about which activities to keep open across a range of social settings and venues guided only by ad hoc heuristics regarding social distancing and personal hygiene. Hence, we propose the dual use of computational fluid dynamic simulations and surrogate aerosol measurements for location-specific assessment of risk of infection across different real-world settings. We propose a 3-tiered risk assessment scheme to facilitate classification of scenarios into risk levels based on simulations and experiments. Threshold values of <54 and >840 viral copies and <5% and >40% of original aerosol concentration are chosen to stratify low, medium, and high risk. This can help prioritize allowable activities and guide implementation of phased lockdowns or re-opening. Using a public bus in Singapore as a case study, we evaluate the relative risk of infection across scenarios such as different activities and passenger positions and demonstrate the effectiveness of our risk assessment methodology as a simple and easily interpretable framework. For example, this study revealed that the bus's air-conditioning greatly influences dispersion and increases the risk of certain seats and that talking can result in similar relative risk to coughing for passengers around an infected person. Both numerical and experimental approaches show similar relative risk levels with a Spearman's correlation coefficient of 0.74 despite differing observables, demonstrating applicability of this risk assessment methodology to other scenarios.

Photocatalytic Rejuvenation Enabled Self-Sanitizing, Reusable, and Biodegradable Masks against COVID-19

Personal protective equipment (PPE) has been highly recommended by the U.S. Centers for Disease Control and Prevention for self-protection during the disastrous SARS-CoV-2 (COVID-19) pandemic. Nevertheless, massive utilization of PPE encounters significant challenges in recycling and sterilizing the used masks. To tackle the associated plastic pollution of used masks, in this work, we designed a reusable, biodegradable, and antibacterial mask. The mask was fabricated by the electrospinning of polyvinyl alcohol (PVA), poly(ethylene oxide) (PEO), and cellulose nanofiber (CNF), followed by esterification and the deposition of a nitrogen-doped TiO2 (N-TiO2) and TiO2 mixture. The fabricated mask containing photocatalytic N-TiO2/TiO2 reached 100% bacteria disinfection under either 0.1 sun simulation (200-2500 nm, 106 W m-2) or natural sunlight for only 10 min. Thus, the used mask can be rejuvenated through light irradiation and reused, which represents one of the handiest technologies for handling used masks. Furthermore, intermolecular interactions between PVA, PEO, and CNF enhanced the electrospinnability and mechanical performance of the resultant mask, which possesses a 10-fold elastic modulus and 2-fold tensile strength higher than a commercial single-use mask. The porous structures of electrospun nanofibers along with strong electrostatic attraction enabled breathability (83.4 L min-1 of air flow rate) and superior particle filterability (98.7%). The prepared mask also had excellent cycling performance, wearability, and stable filtration efficiency even after 120 min wearing. Therefore, this mask could be a great alternative to current masks to address the urgent need for a sustainable, reusable, environmentally friendly, and efficient PPE under the ongoing COVID-19 contagion.

Toward the prevention of coronavirus infection: what role can polymers play?

Severe acute respiratory syndrome-associated coronavirus 2 has caused a global public health crisis with high rates of infection and mortality. Treatment and prevention approaches include vaccine development, the design of small-molecule antiviral drugs, and macromolecular neutralizing antibodies. Polymers have been designed for effective virus inhibition and as antiviral drug delivery carriers. This review summarizes recent progress and provides a perspective on polymer-based approaches for the treatment and prevention of coronavirus infection. These polymer-based partners include polyanion/polycations, dendritic polymers, macromolecular prodrugs, and polymeric drug delivery systems that have the potential to significantly improve the efficacy of antiviral therapeutics.

Compressible and Stretchable Magnetoelectric Sensors Based on Liquid Metals for Highly Sensitive, Self-Powered Respiratory Monitoring

Healthcare monitoring, especially for respiration, has attracted tremendous attention from academics considering the great significance of health information feedback. The respiratory rate, as a critical health indicator, has been used to screen and evaluate potential illness risks in early medical diagnoses. A self-powered sensing system for medical monitoring is critical and imperative due to needless battery replacement and simple assembly. However, the development of a self-powered respiratory sensor with highly sensitive performance is still a daunting challenge. In this work, a compressible and stretchable magnetoelectric sensor (CSMS) with an arch-shaped air gap is reported, enabling self-powered respiratory monitoring driven by exhaled/inhaled breath. The CSMS contains two key functional materials: liquid metals and magnetic powders both with low Young's modulus, allowing for sensing compressibility and stretchability simultaneously. More importantly, such a magnetoelectric sensor exhibits mechanoelectrical converting capacity under an external force, which has been verified by Maxwell numerical simulation. Owing to the air-layer introduction, the magnetoelectric sensors achieve high sensitivity (up to 17.73 kPa^-1), fast response, and long-term stability. The highly sensitive and self-powered magnetoelectric sensor can be further applied as a noninvasive, miniaturized, and portable respiratory monitoring system with the aim of warning for potential health risks. We anticipate that this technique will create an avenue for self-powered respiratory monitoring fields.

The Efficacy of Plant-Based Ionizers in Removing Aerosol for COVID-19 Mitigation

Small-sized droplets/aerosol transmission is one of the factors responsible for the spread of COVID-19, in addition to large droplets and surface contamination (fomites). While large droplets and surface contamination can be relatively easier to deal with (i.e., using mask and proper hygiene measures), aerosol presents a different challenge due to their ability to remain airborne for a long time. This calls for mitigation solutions that can rapidly eliminate the airborne aerosol. Pre-COVID-19, air ionizers have been touted as effective tools to eliminate small particulates. In this work, we sought to evaluate the efficacy of a novel plant-based ionizer in eliminating aerosol. It was found that factors such as the ion concentration, humidity, and ventilation can drastically affect the efficacy of aerosol removal. The aerosol removal rate was quantified in terms of ACH (air changes per hour) and CADR- (clean air delivery rate-) equivalent unit, with ACH as high as 12 and CADR as high as 141 ft³/minute being achieved by a plant-based ionizer in a small isolated room. This work provides an important and timely guidance on the effective deployment of ionizers in minimizing the risk of COVID-19 spread via airborne aerosol, especially in a poorly-ventilated environment.

Emerging Telemedicine Tools for Remote COVID-19 Diagnosis, Monitoring, and Management

The management of the COVID-19 pandemic has relied on cautious contact tracing, quarantine, and sterilization protocols while we await a vaccine to be made widely available. Telemedicine or mobile health (mHealth) is well-positioned during this time to reduce potential disease spread and prevent overloading of the healthcare system through at-home COVID-19 screening, diagnosis, and monitoring. With the rise of mass-fabricated electronics for wearable and portable sensors, emerging telemedicine tools have been developed to address shortcomings in COVID-19 diagnostics, monitoring, and management. In this Perspective, we summarize current implementations of mHealth sensors for COVID-19, highlight recent technological advances, and provide an overview on how these tools may be utilized to better control the COVID-19 pandemic.