Advancements in Nanofiber-Based Electrochemical Biosensors for Diagnostic Applications.

Biosensors are analytical tools that can be used as simple, real-time, and effective devices in clinical diagnosis, food analysis, and environmental monitoring. Nanoscale functional materials possess unique properties such as a large surface-to-volume ratio, making them useful for biomedical diagnostic purposes. Nanoengineering has resulted in the increased use of nanoscale functional materials in biosensors. Various types of nanostructures i.e., 0D, 1D, 2D, and 3D, have been intensively employed to enhance biosensor selectivity, limit of detection, sensitivity, and speed of response time to display results. In particular, carbon nanotubes and nanofibers have been extensively employed in electrochemical biosensors, which have become an interdisciplinary frontier between material science and viral disease detection. This review provides an overview of the current research activities in nanofiber-based electrochemical biosensors for diagnostic purposes. The clinical applications of these nanobiosensors are also highlighted, along with a discussion of the future directions for these materials in diagnostics. The aim of this review is to stimulate a broader interest in developing nanofiber-based electrochemical biosensors and improving their applications in disease diagnosis. In this review, we summarize some of the most recent advances achieved in point of care (PoC) electrochemical biosensor applications, focusing on new materials and modifiers enabling biorecognition that have led to improved sensitivity, specificity, stability, and response time.

Feature Adaptation Predictive Coding for Quantized Block Compressive Sensing of COVID-19 X-Ray Images

With the development of remote X-ray detection for Corona Virus Disease 2019 (COVID-19), the quantized block compressive sensing technology plays an important role when remotely acquiring the chest X-ray images of COVID-19 infected people and significantly promoting the portable telemedicine imaging applications. In order to improve the encoding performance of quantized block compressive sensing, a feature adaptation predictive coding (FAPC) method is proposed for the remote transmission of COVID-19 X-ray images. The proposed FAPC method can adaptively calculate the block-wise prediction coefficients according to the main features of COVID-19 X-ray images, and thus provide the optimal prediction candidate from the feature-guided candidate set. The proposed method can implement the high-efficiency encoding of X-ray images, and then swiftly transmit the telemedicine-oriented chest images. The experimental results show that compared with the state-of-the-art predictive coding methods, both rate-distortion and complexity performance of our FAPC method have enough competitive advantages. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review

Management of crowd information in public transportation (PT) systems is crucial, both to foster sustainable mobility, by increasing the user's comfort and satisfaction during normal operation, as well as to cope with emergency situations, such as pandemic crises, as recently experienced with coronavirus disease (COVID-19) limitations. This article presents a taxonomy and review of sensing technologies based on the Internet of Things (IoT) for real-time crowd analysis, which can be adopted in the different segments of the PT system (buses/trams/trains, railway/metro stations, and bus/tram stops). To discuss such technologies in a clear systematic perspective, we introduce a reference architecture for crowd management, which employs modern information and communication technologies (ICTs) in order to: 1) monitor and predict crowding events;2) implement crowd-aware policies for real-time and adaptive operation control in intelligent transportation systems (ITSs);and 3) inform in real time the users of the crowding status of the PT system, by means of electronic displays installed inside vehicles or at bus/tram stops/stations and/or by mobile transport applications. It is envisioned that the innovative crowd management functionalities enabled by ICT/IoT sensing technologies can be incrementally implemented as an add-on to state-of-the-art ITS platforms, which are already in use by major PT companies operating in urban areas. Moreover, it is argued that, in this new framework, additional services can be delivered to the passengers, such as online ticketing, vehicle access control and reservation in severely crowded situations, and evolved crowd-aware route planning. © 2001-2012 IEEE.

Sensing Technologies for Oxygen Therapy Monitoring: A Survey

Supplemental oxygen is recognized worldwide as a life-saving treatment for first aid, acute and chronic diseases, and this has recently become more important than ever, due to the recent Covid-19 pandemic. This study aims to analyze two important issues related to oxygen therapy in patients with respiratory difficulties, namely oxygen quality and patient safety monitoring. The specific case in which the supply of oxygen fails due to the disconnection of the nasal cannula has no solution in the open literature. As a result, tangible results on how such risk can be avoided are still missing, and hardly any guideline can be found on how to treat this issue from the engineering perspective. In this respect, this work is dedicated to exploring sensing technologies used to detect vital signs and track the patient's condition in real time during therapy, with the aim of defining a starting picture of the current state of the art. The results obtained following the verification of some of the most used sensors in the market are therefore presented and discussed. The integration of these components in an embedded system has also allowed us to understand the practical limits and strengths in terms of complexity and effectiveness of each technology. © 2022 IEEE.

A Low-Cost In-situ System for Continuous Multi-Person Fever Screening

With the recent societal impact of COVID-19, companies and government agencies alike have turned to thermal camera based skin temperature sensing technology to help screen for fever. However, the cost and deployment restrictions limit the wide use of these thermal sensing technologies. In this work, we present SIFTER, a low-cost system based on a RGB-thermal camera for continuous fever screening of multiple people. This system detects and tracks heads in the RGB and thermal domains and constructs thermal heat map models for each tracked person, and classifies people as having or not having fever. SIFTER can obtain key temperature features of heads in-situ at a distance and produce fever screening predictions in real-time, significantly improving screening through-put while minimizing disruption to normal activities. In our clinic deployment, SIFTER measurement error is within 0.4°F at 2 meters and around 0.6°F at 3.5 meters. In comparison, most infrared thermal scanners on the market costing several thousand dollars have around 1°F measurement error measured within 0.5 meters. SIFTER can achieve 100% true positive rate with 22.5% false positive rate without requiring any human interaction, greatly outperforming our baseline [1], which sees a false positive rate of 78.5%. © 2022 IEEE.

SARS-CoV-2 PROTEINS AND BIOTOXIN DETECTION USING PHOTONIC RESONATOR SENSOR

The great advances in silicon photonic-sensing technology have made it an attractive platform for wide sensing applications. The small size of chip and detection system makes photonic microring resonator can be used in clinic for quick detection of disease. Here, we employ the high sensitivity of the photonic sensor toward the change of refractive index for the detection of SARS-CoV-2 virus spike proteins and botulinum toxin in water. The system require very small amount of sample 50uL with high sensitivity, in short 1hr without pre-treatment required. The measurement can be automatic with minimum manpower involved. Moreover, the system can be multiplexed to detect a few target analytes at the same time in one sample. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

Advanced Pedestrian State Sensing Method for Automated Patrol Vehicle Based on Multi-Sensor Fusion.

At present, the COVID-19 pandemic still presents with outbreaks occasionally, and pedestrians in public areas are at risk of being infected by the viruses. In order to reduce the risk of cross-infection, an advanced pedestrian state sensing method for automated patrol vehicles based on multi-sensor fusion is proposed to sense pedestrian state. Firstly, the pedestrian data output by the Euclidean clustering algorithm and the YOLO V4 network are obtained, and a decision-level fusion method is adopted to improve the accuracy of pedestrian detection. Then, combined with the pedestrian detection results, we calculate the crowd density distribution based on multi-layer fusion and estimate the crowd density in the scenario according to the density distribution. In addition, once the crowd aggregates, the body temperature of the aggregated crowd is detected by a thermal infrared camera. Finally, based on the proposed method, an experiment with an automated patrol vehicle is designed to verify the accuracy and feasibility. The experimental results have shown that the mean accuracy of pedestrian detection is increased by 17.1% compared with using a single sensor. The area of crowd aggregation is divided, and the mean error of the crowd density estimation is 3.74%. The maximum error between the body temperature detection results and thermometer measurement results is less than 0.8°, and the abnormal temperature targets can be determined in the scenario, which can provide an efficient advanced pedestrian state sensing technique for the prevention and control area of an epidemic.

Assessment of Holographic Environment for Learning Sensing Technologies in CEM Education

Despite the benefits and suitability of mixed reality as a learning tool for spatial and haptic delivery of educational content, the adaptability of mixed reality for teaching sensing technologies in construction education remains ambiguous. Sensing technologies have potentials to advance construction performance as highlighted by several studies and construction industry reports. To equip future workforce with the required skills, it is important they experientially deploying these technologies on the jobsite. However, institutions are experiencing different constraints such as weather, schedule, and COVID-19 restrictions to provide future workforce with required hands-on learning. The study argues the pedagogical value of a mixed reality learning environment for teaching sensing technologies through a usability study with construction engineering and management students who are familiar with sensing technologies. The study employed quantitative and subjective users' evaluation through a cognitive walkthrough of the learning environment using a mixed reality head-mounted display. Subjective data were obtained using think-aloud protocol and questionnaires on users' experience. Eye tracking device inbuilt in the mixed reality head-mounted display was employed to monitor the eye gaze movements and provide quantitative data of users' cognitive workload. Results from eye tracking, think-aloud protocol and questionnaires were triangulated to validate findings from the study. The study reveals the ease of use and effectiveness of the environment for learning sensing technologies. The characteristics, benefits, and deficiencies of the learning environment as a pedagogical tool in construction education are further highlighted. © 2021 Computing in Civil Engineering 2021 - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2021. All rights reserved.

Recent developments in the diagnosis of COVID-19 with micro- and nanosystems

The SARS-CoV-2 (new severe acute respiratory syndrome coronavirus 2) pandemic virus has been creating devastating situations across the world and serious outbreaks have been encountering day by day since December 2019. Later, the second phase has been spread to all aged people with its moderate variants. Right from the beginning, many research groups and laboratories are desperately working for the proper solutions to eradicate the SARS-CoV-2 virus. In the year 2020 the vaccine was also developed for the COVID-19 virus from Bharat Biotech. According to the medical reports, the developed vaccine was working properly. Although in spite of having the proper results, again COVID-19 victims have been encountering every day in an uncontrolled manner. However, it has been quite interesting that currently many methodologies are available for the initial stage detection of the COVID-19 virus with accurate results. Among them, real-time polymerase chain reaction technique is gaining much attention in the research laboratories for the detection of this virus. Due to having a sophisticated procedure, a protocol for the sample preparation, and expensive instrumentation, this approach is still not available to everyone. On the other hand, nanotechnology-mediated methodologies are also providing excellent results compared to the conventional approach. Hence, in this chapter we have discussed and summarized nanotechnology-mediated recent developments, procedures, and protocols with possible working mechanisms. We believe that the provided information would be useful for the preparation of new ideas and insights to develop many innovations for the treatment and control of the SARS-CoV-2 virus. © 2021 Elsevier Inc. All rights reserved.

ENHANCING BATHYMETRIC MAPPING CAPABILITY USING MULTI-ZONE ENSEMBLE FITTING: FACILITATING EMERGING POST COVID-19 DEMANDS

Determination of hydrospatial information across the marine environment has conventionally appeased by vessel-based acoustic surveys. For the first time in history, the unpredictability COVID-19 health crisis has shut down the entire social and economic sectors across the globe. The continuous nationwide lockdown has made it very difficult to mobilize vessels and survey crews for bathymetric mapping. With the emerging remote sensing technology, hydrospatial specialists today have too accustomed to live and work in the new normality. Apparently, hydrography is clearly undergoing dramatic change which an expanded role to serve an increasing number of stakeholders in the blue economy. In order to seek the maximum benefits from the adoption of forth industrial revolution (IR4.0) paradigms, utilization of high-technology sensors and various unmanned autonomous crafts for bathymetric data acquisition to generate actionable data and information to serve the hydrographic communities. In response to the COVID-19 outbreak, hydrographic communities have been forced to accelerate the adoption of emerging technologies to mitigate its impact. Indeed, satellite derived bathymetry (SDB) has become a recognized tool for acquisition to generate actionable hydrospatial data that can alleviate future economic upheavals. Stakeholders are able to extract the bathymetric depth information from the remotely sensed imagery in a split second without physical mobilization and on-site survey. In this paper a new proposed methodology using multi-zone ensemble fitting is introduced for bathymetric determination across the coastal region from high resolution satellite images. By segmentizing the training sets to fit into several designated depth zones, this sequential ensemble fitting approach demonstrates better performance if compares to the traditional single regression algorithm. Derived conclusion points out that newly proposed method can enhance the current bathymetric mapping capability and deliver precise and accurate actionable hydrospatial information in facilitating the emerging demands, in the post COVID-19 era. © ACRS 2021.All right reserved.

Development stage of novel digital health interventions for postoperative monitoring: protocol of a systematic review.

Introduction: The postoperative period represents a time where patients are at a high-risk of morbidity, which warrants effective surveillance. While digital health interventions (DHIs) for postoperative monitoring are promising, a coordinated, standardized and evidence-based approach regarding their implementation and evaluation is currently lacking. This study aimed to identify DHIs implemented and evaluated in postoperative care to highlight research gaps and assess the readiness for routine implementation. Methods: A systematic review will be conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify studies describing the implementation and evaluation of DHIs for postoperative monitoring published since 2000 (PROSPERO ID: CRD42021264289). This will encompass the Embase, Cumulative Index to Nursing and Allied Health Literature, Cochrane Library, Web of Science and ClinicalTrials.gov databases, and manual search of bibliographies for relevant studies and gray literature. Methodological reporting quality will be evaluated using the Idea, Development, Exploration, Assessment and Long-term Follow-up (IDEAL) reporting guideline relevant to the IDEAL stage of the study, and risk of bias will be assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) framework. Data will be extracted according to the WHO framework for monitoring and evaluating DHIs, and a narrative synthesis will be performed. Discussion: This review will assess the readiness for implementation of DHIs for routine postoperative monitoring and will include studies describing best practice from service changes already being piloted out of necessity during the COVID-19 pandemic. This will identify interventions with sufficient evidence to progress to the next IDEAL stage, and promote standardized and comprehensive evaluation of future implementational studies.

A scoping review of mHealth monitoring of pediatric bronchial asthma before and during COVID-19 pandemic.

Mobile (m) Health technology is well-suited for Remote Patient Monitoring (RPM) in a patient's habitual environment. In recent years there have been fast-paced developments in mHealth-enabled pediatric RPM, especially during the COVID-19 pandemic, necessitating evidence synthesis. To this end, we conducted a scoping review of clinical trials that had utilized mHealth-enabled RPM of pediatric asthma. MEDLINE, Embase and Web of Science were searched from September 1, 2016 through August 31, 2021. Our scoping review identified 25 publications that utilized synchronous and asynchronous mHealth-enabled RPM in pediatric asthma, either involving mobile applications or via individual devices. The last three years has seen the development of evidence-based, multidisciplinary, and participatory mHealth interventions. The quality of the studies has been improving, such that 40% of included study reports were randomized controlled trials. In conclusion, there exists high-quality evidence on mHealth-enabled RPM in pediatric asthma, warranting future systematic reviews and/or meta-analyses of the benefits of such RPM.

Tracking metabolic responses based on macronutrient consumption: A comprehensive study to continuously monitor and quantify dual markers (cortisol and glucose) in human sweat using WATCH sensor.

Wearable Awareness Through Continuous Hidrosis (WATCH) sensor is a sweat based monitoring platform that tracks cortisol and glucose for the purpose of understanding metabolic responses related to macronutrient consumption. In this research article, we have demonstrated the ability of tracking these two biomarkers in passive human sweat over a workday period (8 h) for 10 human subjects in conjunction with their macronutrient consumption. The validation of the WATCH sensor performance was carried out via standard reference methods such as Luminex and ELISA This is a first demonstration of a passive sweat sensing technology that can detect interrelated dual metabolites, cortisol, and glucose, on a single sensing platform. The significance of detecting the two biomarkers simultaneously is that capturing the body's metabolic and endocrinal responses to dietary triggers can lead to improved lifestyle management. For sweat cortisol, we achieved a detection limit of 1 ng/ml (range ∼1-12.5 ng/ml) with Pearson's "r" of 0.897 in reference studies and 0.868 in WATCH studies. Similarly, for sweat glucose, we achieved a detection limit of 1 mg/dl (range ∼ 1-11 mg/dl) with Pearson's "r" of 0.968 in reference studies and 0.947 in WATCH studies, respectively. The statistical robustness of the WATCH sensor was established through the Bland-Altman analysis, whereby the sweat cortisol and sweat glucose levels are comparable to the standard reference method. The probability distribution (t-test), power analysis (power 0.82-0.87), α = 0.05. Mean absolute relative difference (MARD) outcome of Ë·5.10-5.15% further confirmed the statistical robustness of the sweat sensing WATCH device output.

Continuous monitoring in COVID-19 care: a retrospective study in time of crisis.

BACKGROUND: A new monitoring system was implemented to support nursing staff and physicians on the COVID-19 ward. This system was designed to remotely monitor vital signs, to calculate an automated Early Warning Score, and to help identify patients at risk of deterioration. METHODS: Hospitalized patients who tested positive for SARS-CoV-2 were connected to 2 wireless sensors measuring vital signs. Patients were divided into 2 groups based on the occurrence of adverse events during hospitalization. Heart and respiratory rate were monitored continuously and an automated EWS was calculated every 5 minutes. Data were compared between groups. RESULTS: Prior to the occurrence of adverse events, significantly higher median heart and respiration rate and significantly lower median SPO2 values were observed. Mean and median automated EWS were significantly higher in patients with an adverse event. CONCLUSION: Continuous monitoring systems might help to detect clinical deterioration in COVID-19 patients at an earlier stage.

The pilot, proof of concept REMOTE-COVID trial: remote monitoring use in suspected cases of COVID-19 (SARS-CoV 2).

BACKGROUND: SARS-CoV-2 has ever-increasing attributed deaths. Vital sign trends are routinely used to monitor patients with changes in these parameters preceding an adverse event. Wearable sensors can measure vital signs continuously and remotely, outside of hospital facilities, recognising early clinical deterioration. We aim to determine the feasibility & acceptability of remote monitoring systems for quarantined individuals in a hotel suspected of COVID-19. METHODS: A pilot, proof-of-concept, feasibility trial was conducted in engineered hotels near London airports (May-June 2020). Individuals arriving to London with mild suspected COVID-19 symptoms requiring quarantine, as recommended by Public Health England, or healthcare professionals with COVID-19 symptoms unable to isolate at home were eligible. The SensiumVitals™ patch, measuring temperature, heart & respiratory rates, was applied on arrival for the duration of their stay. Alerts were generated when pre-established thresholds were breeched; trained nursing staff could consequently intervene. RESULTS: Fourteen individuals (M = 7, F = 7) were recruited; the mean age was 34.9 (SD 11) years. Mean length of stay was 3 (SD 1.8) days. In total, 10 vital alerts were generated across 4 participants, resulting in telephone contact, reassurance, or adjustment of the sensor. No individuals required hospitalisation or virtual general practitioner review. DISCUSSION: This proof-of-concept trial demonstrated the feasibility of a rapidly implemented model of healthcare delivery through remote monitoring during a pandemic at a hotel, acting as an extension to a healthcare trust. Benefits included reduced viral exposure to healthcare staff, with recognition of clinical deterioration through ambulatory, continuous, remote monitoring using a discrete wearable sensor. CONCLUSION: Remote monitoring systems can be applied to hotels to deliver healthcare safely in individuals suspected of COVID-19. Further work is required to evaluate this model on a larger scale. TRIAL REGISTRATION: Clinical trials registration information: ClinicalTrials.gov Identifier: NCT04337489 (07/04/2020).

The Use of Telehealth Technology to Support Health Coaching for Older Adults: Literature Review.

BACKGROUND: Health coaching is an intervention process for driving behavior change through goal-setting, education, encouragement, and feedback on health-related behaviors. Telehealth systems that include health coaching and remote monitoring are making inroads in managing chronic conditions and may be especially suited for older populations. OBJECTIVE: This literature review aimed to investigate the current status of health coaching interventions incorporating telehealth technology and the associated effectiveness of this intervention to deliver health care with an emphasis on older adults (aged 65 and older). METHODS: A literature review was conducted to identify the research conducted on health coaching combined with remote monitoring for delivering health care to older adults. The Ovid MEDLINE and CINAHL databases were queried using a combination of relevant search terms (including middle aged, aged, older adult, elderly, health coaching, and wellness coaching). The search retrieved 196 papers published from January 2010 to September 2019 in English. Following a systematic review process, the titles and abstracts of the papers retrieved were screened for applicability to health coaching for older adults to define a subset for further review. Papers were excluded if the studied population did not include older adults. The full text of the 42 papers in this subset was then reviewed, and 13 papers related to health coaching combined with remote monitoring for older adults were included in this review. RESULTS: Of the 13 studies reviewed, 10 found coaching supported by telehealth technology to provide effective outcomes. Effectiveness outcomes assessed in the studies included hospital admissions/re-admissions, mortality, hemoglobin A1c (HbA1c) level, body weight, blood pressure, physical activity level, fatigue, quality of life, and user acceptance of the coaching program and technology. CONCLUSIONS: Telehealth systems that include health coaching have been implemented in older populations as a viable intervention method for managing chronic conditions with mixed results. Health coaching combined with telehealth may be an effective solution for providing health care to older adults. However, health coaching is predominantly performed by human coaches with limited use of technology to augment or replace the human coach. The opportunity exists to expand health coaching to include automated coaching.

Smart Patch for Skin Temperature: Preliminary Study to Evaluate Psychometrics and Feasibility.

There is a need for continuous, non-invasive monitoring of biological data to assess health and wellbeing. Currently, many types of smart patches have been developed to continuously monitor body temperature, but few trials have been completed to evaluate psychometrics and feasibility for human subjects in real-life scenarios. The aim of this feasibility study was to evaluate the reliability, validity and usability of a smart patch measuring body temperature in healthy adults. The smart patch consisted of a fully integrated wearable wireless sensor with a multichannel temperature sensor, signal processing integrated circuit, wireless communication feature and a flexible battery. Thirty-five healthy adults were recruited for this test, carried out by wearing the patches on their upper chests for 24 h and checking their body temperature six times a day using infrared forehead thermometers as a gold standard for testing validity. Descriptive statistics, one-sampled and independent t-tests, Pearson's correlation coefficients and Bland-Altman plot were examined for body temperatures between two measures. In addition, multiple linear regression, receiver operating characteristic (ROC) and qualitative content analysis were conducted. Among the 35 participants, 29 of them wore the patch for over 19 h (dropout rate: 17.14%). Mean body temperature measured by infrared forehead thermometers and smart patch ranged between 32.53 and 38.2 °C per person and were moderately correlated (r = 0.23-0.43) overall. Based on a Bland-Altman plot, approximately 94% of the measurements were located within one standard deviation (upper limit = 4.52, lower limit = -5.82). Most outliers were identified on the first measurement and were located below the lower limit. It is appropriate to use 37.5 °C in infrared forehead temperature as a cutoff to define febrile conditions. Users' position while checking and ambient temperature and humidity are not affected to the smart patch body temperature. Overall, the participants showed high usability and satisfaction on the survey. Few participants reported discomfort due to limited daily activity, itchy skin or detaching concerns. In conclusion, epidermal electronic sensor technologies provide a promising method for continuously monitoring individuals' body temperatures, even in real-life situations. Our study findings show the potential for smart patches to monitoring non-febrile condition in the community.

Design of the pilot, proof of concept REMOTE-COVID trial: remote monitoring use in suspected cases of COVID-19 (SARS-CoV-2).

BACKGROUND: The outbreak of SARS-CoV-2 (coronavirus, COVID-19), declared a pandemic by the World Health Organization (WHO), is a global health problem with ever-increasing attributed deaths. Vital sign trends are routinely used to monitor patients with changes in these parameters often preceding an adverse event. Wearable sensors can measure vital signs continuously (e.g. heart rate, respiratory rate, temperature) remotely and can be utilised to recognise early clinical deterioration. METHODS: We describe the protocol for a pilot, proof-of-concept, observational study to be conducted in an engineered hotel near London airports, UK. The study is set to continue for the duration of the pandemic. Individuals arriving to London with mild symptoms suggestive of COVID-19 or returning from high-risk areas requiring quarantine, as recommended by the Public Health England, or healthcare professionals with symptoms suggestive of COVID-19 unable to isolate at home will be eligible for a wearable patch to be applied for the duration of their stay. Notifications will be generated should deterioration be detected through the sensor and displayed on a central monitoring hub viewed by nursing staff, allowing for trend deterioration to be noted. The primary objective is to determine the feasibility of remote monitoring systems in detecting clinical deterioration for quarantined individuals in a hotel. DISCUSSION: This trial should prove the feasibility of a rapidly implemented model of healthcare delivery through remote monitoring during a global pandemic at a hotel, acting as an extension to a healthcare trust. Potential benefits would include reducing infection risk of COVID-19 to healthcare staff, with earlier recognition of clinical deterioration through ambulatory, continuous, remote monitoring using a discrete wearable sensor. We hope our results can power future, robust randomised trials. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04337489 .

Available Technologies, Applications and Benefits of Teleorthodontics. A Literature Review and Possible Applications during the COVID-19 Pandemic.

BACKGROUND: COVID-2019 spread rapidly throughout the world from China. This infection is highly contagiousness, has a high morbidity, and is capable of evolving into a potentially lethal form of interstitial pneumonia. Numerous countries shut-down various activities that were considered "not essential." Dental treatment was in this category and, at the time of writing, only non-deferrable emergencies are still allowed in many countries. Therefore, follow-up visits of ongoing active therapies (e.g., orthodontic treatment) must be handled taking special precautions. This literature review aims at reducing in-office appointments by providing an overview of the technologies available and their reliability in the long-distance monitoring of patients, i.e., teledentistry. METHODS: A literature review was made according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) guidelines. Randomized clinical trials, cross sectional, observational, and case-control studies were evaluated with the Mixed Methods Appraisal Tool for quality assessment and study limitations. RESULTS: A primary search found 80 articles, 69/80 were excluded as non-relevant on the basis of: the abstract, title, study design, bias, and/or lack of relevance. Twelve articles were included in the qualitative analysis. CONCLUSIONS: Teleorthodontics can manage most emergencies, reassuring and following patients remotely. The aim set by dental teleassistance was met as it reduced patients' office visits whilst maintaining regular monitoring, without compromising the results. Although our preliminary findings should be further investigated to objectively evaluate the efficacy, cost-effectiveness, and long-term results, we are confident that teleassistance in orthodontics will have a role to play in the near future.