Engineering Magnetic Soft and Reconfigurable Robots.

Magnetic control has gained popularity recently due to its ability to enhance soft robots with reconfigurability and untethered maneuverability, among other capabilities. Several advancements in the fabrication and application of reconfigurable magnetic soft robots have been reported. This review summarizes novel fabrication techniques for designing magnetic soft robots, including chemical and physical methods. Mechanisms of reconfigurability and deformation properties are discussed in detail. The maneuverability of magnetic soft robots is then briefly discussed. Finally, the present challenges and possible future work in designing reconfigurable magnetic soft robots for biomedical applications are identified.

EgoActive: Integrated Wireless Wearable Sensors for Capturing Infant Egocentric Auditory-Visual Statistics and Autonomic Nervous System Function 'in the Wild'.

There have been sustained efforts toward using naturalistic methods in developmental science to measure infant behaviors in the real world from an egocentric perspective because statistical regularities in the environment can shape and be shaped by the developing infant. However, there is no user-friendly and unobtrusive technology to densely and reliably sample life in the wild. To address this gap, we present the design, implementation and validation of the EgoActive platform, which addresses limitations of existing wearable technologies for developmental research. EgoActive records the active infants' egocentric perspective of the world via a miniature wireless head-mounted camera concurrently with their physiological responses to this input via a lightweight, wireless ECG/acceleration sensor. We also provide software tools to facilitate data analyses. Our validation studies showed that the cameras and body sensors performed well. Families also reported that the platform was comfortable, easy to use and operate, and did not interfere with daily activities. The synchronized multimodal data from the EgoActive platform can help tease apart complex processes that are important for child development to further our understanding of areas ranging from executive function to emotion processing and social learning.

Actuation technologies for magnetically guided catheters.

Due to their wide range of clinical application possibilities, magnetic actuation technologies have grabbed the attention of researchers worldwide. The design, execution, and analysis of magnetic catheter systems have advanced significantly during the last decade. The review focuses on magnetic actuation for catheter steering and control of the device, which will be explored in detail in the following sections. There is a discussion of future work and the challenges of the review systems, and the conclusions are finally addressed.

Reshaping healthcare with wearable biosensors.

Wearable health sensors could monitor the wearer's health and surrounding environment in real-time. With the development of sensor and operating system hardware technology, the functions of wearable devices have been gradually enriched with more diversified forms and more accurate physiological indicators. These sensors are moving towards high precision, continuity, and comfort, making great contributions to improving personalized health care. At the same time, in the context of the rapid development of the Internet of Things, the ubiquitous regulatory capabilities have been released. Some sensor chips are equipped with data readout and signal conditioning circuits, and a wireless communication module for transmitting data to computer equipment. At the same time, for data analysis of wearable health sensors, most companies use artificial neural networks (ANN). In addition, artificial neural networks could help users effectively get relevant health feedback. Through the physiological response of the human body, various sensors worn could effectively transmit data to the control unit, which analyzes the data and provides feedback of the health value to the user through the computer. This is the working principle of wearable sensors for health. This article focuses on wearable biosensors used for healthcare monitoring in different situations, as well as the development, technology, business, ethics, and future of wearable sensors for health monitoring.

MR conditional prostate intervention systems and actuations review.

Magnetic resonance imaging (MRI) has the ability to provide high-resolution images of soft tissues without the use of radiation. So much research has been focused on the development of actuators and robotic devices that can be used in the MRI environment so "real-time" images can be obtained during surgeries. With real-time guidance from MRI, robots can perform surgical procedures with high accuracy and through less invasive routes. This technique can also significantly reduce the operation time and simplify pre-surgical procedures. Therefore, research on robot-assisted MRI-guided prostate intervention has attracted a great deal of interest, and several successful clinical trials have been published in recent years, pointing to the great potential of this technology. However, the development of MRI-guided robots is still in the primary stage, and collaboration between researchers and commercial suppliers is still needed to improve such robot systems. This review presents an overview of MRI-guided prostate intervention devices and actuators. Additionally, the expected technical challenges and future advances in this field are discussed.

Engineering functional and anthropomorphic models for surgical training in interventional radiology: A state-of-the-art review.

Training medical students in surgical procedures and evaluating their performance are both necessary steps to ensure the safety and efficacy of surgeries. Traditionally, trainees practiced on live patients, cadavers or animals under the supervision of skilled physicians, but realistic anatomical phantom models have provided a low-cost alternative because of the advance of material technology that mimics multi-layer tissue structures. This setup provides safer and more efficient training. Many research prototypes of phantom models allow rapid in-house prototyping for specific geometries and tissue properties. The gel-based method and 3D printing-based method are two major methods for developing phantom prototypes. This study excluded virtual reality based technologies and focused on physical phantoms, total 189 works published between 2015 and 2020 on anatomical phantom prototypes made for interventional radiology were reviewed in terms of their functions and applications. The phantom prototypes were first categorized based on fabrication methods and then subcategorized based on the organ or body part they simulated; the paper is organized accordingly. Engineering specifications and applications were analyzed and summarized for each study. Finally, current challenges in the development of phantom models and directions for future work were discussed.

Supporting Technologies for COVID-19 Prevention: Systemized Review.

Background: During COVID-19, clinical and health care demands have been on the rapid rise. Major challenges that have arisen during the pandemic have included a lack of testing kits, shortages of ventilators to treat severe cases of COVID-19, and insufficient accessibility to personal protective equipment for both hospitals and the public. New technologies have been developed by scientists, researchers, and companies in response to these demands. Objective: The primary objective of this review is to compare different supporting technologies in the subjugation of the COVID-19 spread. Methods: In this paper, 150 news articles and scientific reports on COVID-19-related innovations during 2020-2021 were checked, screened, and shortlisted to yield a total of 23 articles for review. The keywords "COVID-19 technology," "COVID-19 invention," and "COVID-19 equipment" were used in a Google search to generate related news articles and scientific reports. The search was performed on February 1, 2021. These were then categorized into three sections, which are personal protective equipment (PPE), testing methods, and medical treatments. Each study was analyzed for its engineering characteristics and potential social impact on the COVID-19 pandemic. Results: A total of 9 articles were selected for review concerning PPE. In general, the design and fabrication of PPE were moving toward the direction of additive manufacturing and intelligent information feedback while being eco-friendly. Moreover, 8 articles were selected for reviewing testing methods within the two main categories of molecular and antigen tests. All the inventions endeavored to increase sensitivity while reducing the turnaround time. However, the inventions reported in this review paper were not sufficiently tested for their safety and efficiency. Most of the inventions are temporary solutions intended to be used only during shortages of medical resources. Finally, 6 articles were selected for the review of COVID-19 medical treatment. The major challenge identified was the uncertainty in applying novel ideas to speed up the production of ventilators. Conclusions: The technologies developed during the COVID-19 pandemic were considered for review. In order to better respond to future pandemics, national reserves of critical medical supplies should be increased to improve preparation. This pandemic has also highlighted the need for the automation and optimization of medical manufacturing.

Monitoring Different Social Media Platforms to Report Unplanned School Closures Due to Wildfires in California, October and December 2017.

OBJECTIVE: Researchers at the Centers for Disease Control and Prevention monitor unplanned school closure (USC) reports through online systematic searches (OSS) to assist public health emergency responses. We counted the additional reports identified through social media along with OSS to improve USC monitoring. METHODS: Facebook and Twitter data of public-school districts and private schools in counties affected by California wildfires in October and December of 2017 and January of 2018 were retrieved. We computed descriptive statistics and performed multivariable logistic regression for both OSS and social media data. RESULTS: Among the 362 public-school districts in wildfire-affected counties, USCs were identified for 115 (32%) districts, of which OSS identified 104 (90%), Facebook, 59 (52%), and Twitter, 37 (32%). These data correspond to 4622 public schools, among which USCs were identified for 888 (19.2%) schools, of which OSS identified 722 (81.3%), Facebook, 496 (55.9%), and Twitter, 312 (35.1%). Among 1289 private schools, USCs were identified for 104 schools, of which OSS identified 47 (45.2%), Facebook, 67 (64.4%), and Twitter, 29 (27.9%). USC announcements identified via social media, in addition to those via OSS, were 11 public school districts, 166 public schools, and 57 private schools. CONCLUSION: Social media complements OSS as additional resources for USC monitoring during disasters.

Angular needle tracker and stabilizer for image-guided interventions.

INTRODUCTION: Minimally invasive image-guided interventions have changed the face of procedural medicine. For these procedures, safety and efficacy depend on precise needle placement. Needle targeting devices help improve the accuracy of needle placement, but their use has not seen broad penetration. Some of these devices are costly and require major modifications to the clinical workflow. In this article, we developed a low-cost, disposable, and easy-to-use angulation tracking device, which was based on a redesigned commercial passive needle holder. MATERIAL AND METHODS: The new design provided real-time angulation information for needle tracking. In this design, two potentiometers were used as angulation sensors, and they were connected to two axes of the passive needle holder's arch structure through a 3 D-printed bridge structure. A control unit included an Arduino Pro Mini, a Bluetooth module, and two rechargeable batteries. The angulation was calculated and communicated in real time to a novel developed smartphone app, where real-time angulation information was displayed for guiding the operator to position the needle to the planned angles. RESULTS: The open-air test results showed that the average errors are 1.03° and 1.08° for left-right angulation and head-foot angulation, respectively. The animal cadaver tests revealed that the novel system had an average angular error of 3.2° and a radial distance error of 3.1 mm. CONCLUSIONS: The accuracy was comparable with some commercially available solutions. The novel and low-cost needle tracking device may find a role as part of a real-time precision approach to both planning and implementation of image-guided therapies.

Applications of Robotics, Artificial Intelligence, and Digital Technologies During COVID-19: A Review.

Many countries have enacted a quick response to the unexpected coronavirus disease 2019 (COVID-19) pandemic by using existing technologies. For example, robotics, artificial intelligence, and digital technology have been deployed in hospitals and public areas for maintaining social distancing, reducing person-to-person contact, enabling rapid diagnosis, tracking virus spread, and providing sanitation. In this study, 163 news articles and scientific reports on COVID-19-related technology adoption were screened, shortlisted, categorized by application scenario, and reviewed for functionality. Technologies related to robots, artificial intelligence, and digital technology were selected from the pool of candidates, yielding a total of 50 applications for review. Each case was analyzed for its engineering characteristics and potential impact on the COVID-19 pandemic. Finally, challenges and future directions regarding the response to this pandemic and future pandemics were summarized and discussed.

Aggregating Twitter Text through Generalized Linear Regression Models for Tweet Popularity Prediction and Automatic Topic Classification.

Social media platforms have become accessible resources for health data analysis. However, the advanced computational techniques involved in big data text mining and analysis are challenging for public health data analysts to apply. This study proposes and explores the feasibility of a novel yet straightforward method by regressing the outcome of interest on the aggregated influence scores for association and/or classification analyses based on generalized linear models. The method reduces the document term matrix by transforming text data into a continuous summary score, thereby reducing the data dimension substantially and easing the data sparsity issue of the term matrix. To illustrate the proposed method in detailed steps, we used three Twitter datasets on various topics: autism spectrum disorder, influenza, and violence against women. We found that our results were generally consistent with the critical factors associated with the specific public health topic in the existing literature. The proposed method could also classify tweets into different topic groups appropriately with consistent performance compared with existing text mining methods for automatic classification based on tweet contents.

AI-Assisted CT as a Clinical and Research Tool for COVID-19.

There is compelling support for widening the role of computed tomography (CT) for COVID-19 in clinical and research scenarios. Reverse transcription polymerase chain reaction (RT-PCR) testing, the gold standard for COVID-19 diagnosis, has two potential weaknesses: the delay in obtaining results and the possibility of RT-PCR test kits running out when demand spikes or being unavailable altogether. This perspective article discusses the potential use of CT in conjunction with RT-PCR in hospitals lacking sufficient access to RT-PCR test kits. The precedent for this approach is discussed based on the use of CT for COVID-19 diagnosis and screening in the United Kingdom and China. The hurdles and challenges are presented, which need addressing prior to realization of the potential roles for CT artificial intelligence (AI). The potential roles include a more accurate clinical classification, characterization for research roles and mechanisms, and informing clinical trial response criteria as a surrogate for clinical outcomes.

Using Twitter to Track Unplanned School Closures: Georgia Public Schools, 2015-17.

OBJECTIVES: To aid emergency response, Centers for Disease Control and Prevention (CDC) researchers monitor unplanned school closures (USCs) by conducting online systematic searches (OSS) to identify relevant publicly available reports. We examined the added utility of analyzing Twitter data to improve USC monitoring. METHODS: Georgia public school data were obtained from the National Center for Education Statistics. We identified school and district Twitter accounts with 1 or more tweets ever posted ("active"), and their USC-related tweets in the 2015-16 and 2016-17 school years. CDC researchers provided OSS-identified USC reports. Descriptive statistics, univariate, and multivariable logistic regression were computed. RESULTS: A majority (1,864/2,299) of Georgia public schools had, or were in a district with, active Twitter accounts in 2017. Among these schools, 638 were identified with USCs in 2015-16 (Twitter only, 222; OSS only, 2015; both, 201) and 981 in 2016-17 (Twitter only, 178; OSS only, 107; both, 696). The marginal benefit of adding Twitter as a data source was an increase in the number of schools identified with USCs by 53% (222/416) in 2015-16 and 22% (178/803) in 2016-17. CONCLUSIONS: Policy-makers may wish to consider the potential value of incorporating Twitter into existing USC monitoring systems.

Rapid prototyping of custom radiocontrast agent markers for computed tomography-guided procedures.

The objective of this study was to evaluate a method for printing a custom radiocontrast agent mixture to develop computed tomography markers of various shapes and sizes for assisting physicians in computed tomography-guided procedures. The radiocontrast agent mixture was designed to be bright in a computed tomography image, able to be extruded from a nozzle as a liquid and transition into a solid, and sufficiently viscous to be extruded through the tip of a needle in a controlled manner. A mixture printing method was developed using a syringe to house the mixture, a syringe pump to extrude the mixture, and a computer numeric control laser cutter to direct the nozzle in the desired path. To assess the efficacy of printing the radiocontrast agent mixture, we printed several designs, collected computed tomography images, and evaluated various physical properties of the printing method and the resulting computed tomography markers. The average line thickness was 1.56 mm (standard deviation of 0.19 mm, n = 30), the infill percentage was 99.9%, and the deviation in roundness was 0.23 mm (n = 30). These results demonstrated the ability of the proposed method to create various types of skin markers, such as dots, lines, and hollow or solid shapes. Additionally, flat printed patterns can be folded to form three-dimensional structures that can be used to guide and support needle insertions.

An inertial measurement unit tracking system for body movement in comparison with optical tracking.

The recent advancement of motion tracking technology offers better treatment tools for conditions, such as movement disorders, as the outcome of the rehabilitation could be quantitatively defined. The accurate and fast angular information output of the inertial measurement unit tracking systems enables the collection of accurate kinematic data for clinical assessment. This article presents a study of a low-cost microelectromechanical system inertial measurement unit-based tracking system in comparison with the conventional optical tracking system. The system consists of seven microelectromechanical system inertial measurement units, which could be mounted on the lower limbs of the subjects. For the feasibility test, 10 human participants were instructed to perform three different motions: walking, running, and fencing lunges when wearing specially designed sleeves. The subjects' lower body movements were tracked using our inertial measurement unit-based system and compared with the gold standard-the NDI Polaris Vega optical tracking system. The results of the angular comparison between the inertial measurement unit and the NDI Polaris Vega optical tracking system were as follows: the average cross-correlation value was 0.85, the mean difference of joint angles was 2.00°, and the standard deviation of joint angles was ± 2.65°. The developed microelectromechanical system-based tracking system provides an alternative low-cost solution to track joint movement. Moreover, it is able to operate on an Android platform and could potentially be used to assist outdoor or home-based rehabilitation.

The Feasibility of Using a Smartphone Magnetometer for Assisting Needle Placement.

Minimally invasive surgical procedures often require needle insertion. For these procedures, efficacy greatly depends on precise needle placement. Many methods, such as optical tracking and electromagnetic tracking, have been applied to assist needle placement by tracking the real-time position information of the needle. Compared with the optical tracking method, electromagnetic tracking is more suitable for minimally invasive surgery since it has no requirement of line-of-sight. However, the devices needed for electromagnetic tracking are usually expensive, which will increase the cost of surgery. In this study, we presented a low-cost smartphone-based permanent magnet tracking method compatible with CT imaging and designed a 3D printed operation platform to assist with needle placement prior to needle insertion during minimally invasive surgery. The needle positioning accuracy of this method was tested in an open air test and a prostate phantom test in a CT environment. For these two tests, the average radial errors were 0.47 and 2.25 mm, respectively, and the standard deviations were 0.29 and 1.63, respectively. The materials and fabrication required for the presented method are inexpensive. Thus, many image-guided therapies may benefit from the presented method as a low-cost option for needle positioning prior to needle insertion.

Public Health Implications of Image-Based Social Media: A Systematic Review of Instagram, Pinterest, Tumblr, and Flickr.

INTRODUCTION: Image-based social media Instagram, Pinterest, Tumblr, and Flickr have become sources of health-related information and tools for health communication. No known systematic review exists that summarizes the existing research and its health implications. METHODS: We searched EBSCOhost Academic Search Complete, PubMed, and Web of Science in January 2016, April 2017, and November 2017, with the following keywords: Pinterest, Instagram, Tumblr, or Flickr. Only public health-related, peer-reviewed research articles were included (excluding surveys of self-reported social media use). RESULTS: Sixty-six research articles were included. All 12 experimental studies used Instagram. Of the 54 observational studies, 38 studied Instagram; 12, Pinterest; 7, Tumblr; and 6, Flickr; some studies investigated more than 1 platform. More than half of the included articles were related to mental health and substance abuse (n = 39, 59%). Other topics included chronic diseases, infectious diseases, surgery, injury prevention, pharmacovigilance, sexual and reproductive health, and adolescent psychology with functional magnetic resonance imaging. DISCUSSION: Public health-oriented research on Instagram, Pinterest, Tumblr, and Flickr is increasing. Most observational studies investigated questions ranging from public perception of diseases or interventions (vaccination) and undesirable media exposure ("echo chamber," distorted body image, underage substance use, and pro-suicide messages) to information dissemination and online engagement (likes and comments). A few studies attempted to use image-based social media as intervention tools, but the results were mainly exploratory. CONCLUSION: More research is needed to study how social media users discuss health through sharing images online, and how public health professionals can communicate effectively using image-sharing social media.

Twitter Conversations and English News Media Reports on Poliomyelitis in Five Different Countries, January 2014 to April 2015.

INTRODUCTION: Twitter and media coverage on poliomyelitis help maintain global support for its eradication. OBJECTIVE: To test our hypothesis that themes of polio-related tweets and media articles would differ by location of interest (hashtag of country name mentioned in the tweet; country name mentioned in media articles) but would be similar to each other (tweets and media articles) for each location of interest. METHODS: We retrospectively examined a 40% random sample of Twitter data containing the hashtag #polio from January 1, 2014, to April 30, 2015 (N = 79,333), from which we extracted 5 subcorpora each with a co-occurring hashtag #India (n = 5027), #Iraq (n = 1238), #Nigeria (n = 1364), #Pakistan (n = 11,427), and #Syria (n = 2952). We also retrieved and categorized 73 polio-related English-language news stories from within the same timeframe. We assessed the association between polio-related English news themes and the Twitter content. Descriptive analyses and unsupervised machine learning (latent Dirichlet allocation modeling) were conducted on the 5 Twitter subcorpora. RESULTS: The results of the latent Dirichlet allocation modeling on the specific subcorpora with country co-occurring hashtags showed significant differences between the 5 countries in terms of content. English mass media content focused largely on violence/conflicts and cases of polio, whereas social media focused on eradication and vaccination efforts along with celebrations. DISCUSSION: Contrary to our hypothesis, our evidence suggests Twitter content differs significantly from English mass media content. Evidence from our study helps inform media monitoring and communications surveillance during global public health crises, such as infectious disease outbreaks, as well as reactions to health promotion campaigns.

Adopting YouTube to Promote Health: Analysis of State Health Departments.

INTRODUCTION: We describe videos posted to the YouTube video-sharing Web site by US state health departments (SHDs) and associated institutional factors. METHODS: YouTube channels from SHDs were identified, their data retrieved, and their videos saved to a playlist on January 10, 2016. Ten randomly sampled videos from each channel were manually coded for topics. The 2012 Association of State and Territorial Health Officials profile survey was used to obtain information on staff, expenditure, and top 5 priorities for each SHD. Descriptive statistics and univariable regression were conducted. RESULTS: Forty-three SHDs had YouTube channels. Together, all SHDs posted 3957 videos, accumulated 12,151,720 views, and gained 6302 subscribers. In total, 415 videos were manually coded. Information about the agency (17.6%), communicable diseases (12.5%), and mother/infant health (8.9%) comprised the largest share of topics. No statistically significant association was observed between the log-transformed number of videos posted on an SHD's YouTube channel and any of the explanatory variables of SHD staffing and expenditure in 2011. The number of full-time employees (r = 0.34, p = 0.03), number of epidemiologists and biostatisticians (r = 0.41, p = 0.01), and 2011 total year expenditure (r = 0.38, p = 0.02) were positively correlated with the log-transformed number of views per YouTube video posted by SHDs. No meaningful patterns of statistical association were observed between the percentage of expenditure on a specific program area and the topics of videos. CONCLUSION: Most SHDs are using YouTube, which provides a unique opportunity for SHDs to disseminate health messages.

How did Ebola information spread on twitter: broadcasting or viral spreading?

BACKGROUND: Information and emotions towards public health issues could spread widely through online social networks. Although aggregate metrics on the volume of information diffusion are available, we know little about how information spreads on online social networks. Health information could be transmitted from one to many (i.e. broadcasting) or from a chain of individual to individual (i.e. viral spreading). The aim of this study is to examine the spreading pattern of Ebola information on Twitter and identify influential users regarding Ebola messages. METHODS: Our data was purchased from GNIP. We obtained all Ebola-related tweets posted globally from March 23, 2014 to May 31, 2015. We reconstructed Ebola-related retweeting paths based on Twitter content and the follower-followee relationships. Social network analysis was performed to investigate retweeting patterns. In addition to describing the diffusion structures, we classify users in the network into four categories (i.e., influential user, hidden influential user, disseminator, common user) based on following and retweeting patterns. RESULTS: On average, 91% of the retweets were directly retweeted from the initial message. Moreover, 47.5% of the retweeting paths of the original tweets had a depth of 1 (i.e., from the seed user to its immediate followers). These observations suggested that the broadcasting was more pervasive than viral spreading. We found that influential users and hidden influential users triggered more retweets than disseminators and common users. Disseminators and common users relied more on the viral model for spreading information beyond their immediate followers via influential and hidden influential users. CONCLUSIONS: Broadcasting was the dominant mechanism of information diffusion of a major health event on Twitter. It suggests that public health communicators can work beneficially with influential and hidden influential users to get the message across, because influential and hidden influential users can reach more people that are not following the public health Twitter accounts. Although both influential users and hidden influential users can trigger many retweets, recognizing and using the hidden influential users as the source of information could potentially be a cost-effective communication strategy for public health promotion. However, challenges remain due to uncertain credibility of these hidden influential users.