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.

Clinical accuracy of infrared temperature measurement devices: a comparison against non-invasive core-body temperature.

During the coronavirus 2019 (COVID-19) pandemic, the implementation of non-contact infrared thermometry (NCIT) became an increasingly popular method of screening body temperature. However, data on the accuracy of these devices and the standardisation of their use are limited. In the current study, the body temperature of non-febrile volunteers was measured using infrared (IR) thermography, IR tympanic thermometry and IR gun thermometry at different facial feature locations and distances and compared with SpotOn core-body temperature. Poor agreement was found between all IR devices and SpotOn measurements (intra-class correlation coefficient <0.8). Bland-Alman analysis showed the narrowest limits of agreement with the IR gun at 3 cm from the forehead (bias = 0.19°C, limits of agreement (LOA): -0.58°C to 0.97°C) and widest with the IR gun at the nose (bias = 1.40°C, LOA: -1.15°C to 3.94°C). Thus, our findings challenge the established use of IR thermometry devices within hospital settings without adequate standard operating procedures to reduce operator error.

Magnetically steerable catheters: State of the art review.

Magnetically steerable catheters (MSCs) have caught the interest of researchers due to their various potential uses in clinical applications, for example, minimally invasive surgery. Many significant advances in the design, implementation and analysis of MSCs have been accomplished in the last decade. This review concentrates on the configurations of current MSCs with an in depth look at control of the device and the specific workspace. This review also evaluates MSCs and references possible future system designs and difficulties. The concept of magnetic manipulation is briefly presented. Then, by category, the MSC is introduced. Following that, a discussion of future works and challenges of the review systems is provided. The conclusions are finally addressed.

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.

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.

Regression model for predicting core body temperature in infrared thermal mass screening.

With fever being one of the most prominent symptoms of COVID-19, the implementation of fever screening has become commonplace around the world to help mitigate the spread of the virus. Non-contact methods of temperature screening, such as infrared (IR) forehead thermometers and thermal cameras, benefit by minimizing infection risk. However, the IR temperature measurements may not be reliably correlated with actual core body temperatures. This study proposed a trained model prediction using IR-measured facial feature temperatures to predict core body temperatures comparable to an FDA-approved product. The reference core body temperatures were measured by a commercially available temperature monitoring system. Optimal inputs and training models were selected by the correlation between predicted and reference core body temperature. Five regression models were tested during the study. The linear regression model showed the lowest minimum-root-mean-square error (RSME) compared with reference temperatures. The temple and nose region of interest (ROI) were identified as optimal inputs. This study suggests that IR temperature data could provide comparatively accurate core body temperature prediction for rapid mass screening of potential COVID cases using the linear regression model. Using linear regression modeling, the non-contact temperature measurement could be comparable to the SpotOn system with a mean SD of ± 0.285 °C and MAE of 0.240 °C.

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.

Towards catheter steering using magnetic tractor beam coupling.

Catheters are used in various clinical applications, and the ability to direct the catheter to the desired location is critical for clinical outcomes. Steerable catheters assist clinicians to access targeted areas, notably the vascular bundles and major vessels, while causing no damage to the surrounding tissue. A novel catheter actuation technology for catheter steering is presented in this study. The technique is simple and relies on three magnetic couples interacting with one another to generate steering motions. A proof-of-concept catheter prototype demonstrated the capacity to remotely steer a catheter over 100 mm of distance and ±45° of angular positioning, showing the potential manoeuvrability for clinical applications. It is feasible to steer a catheter using this three-magnet pair approach with the great potential to be used for catheterisation procedures. The presented mechanism's kinematics and a near-form solution for catheter steering regardless of design factors will be studied in the future.

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.

Image-Guided Robotics for Standardized and Automated Biopsy and Ablation.

Image-guided robotics for biopsy and ablation aims to minimize procedure times, reduce needle manipulations, radiation, and complications, and enable treatment of larger and more complex tumors, while facilitating standardization for more uniform and improved outcomes. Robotic navigation of needles enables standardized and uniform procedures which enhance reproducibility via real-time precision feedback, while avoiding radiation exposure to the operator. Robots can be integrated with computed tomography (CT), cone beam CT, magnetic resonance imaging, and ultrasound and through various techniques, including stereotaxy, table-mounted, floor-mounted, and patient-mounted robots. The history, challenges, solutions, and questions facing the field of interventional radiology (IR) and interventional oncology are reviewed, to enable responsible clinical adoption and value definition via ergonomics, workflows, business models, and outcome data. IR-integrated robotics is ready for broader adoption. The robots are coming!

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.

Augmented reality technology in image-guided therapy: State-of-the-art review.

Image-guided therapies have been on the rise in recent years as they can achieve higher accuracy and are less invasive than traditional methods. By combining augmented reality technology with image-guided therapy, more organs, and tissues can be observed by surgeons to improve surgical accuracy. In this review, 233 publications (dated from 2015 to 2020) on the design and application of augmented reality-based systems for image-guided therapy, including both research prototypes and commercial products, were considered for review. Based on their functions and applications. Sixteen studies were selected. The engineering specifications and applications were analyzed and summarized for each study. Finally, future directions and existing challenges in the field were summarized and discussed.

A body-mounted device for MRI-guided spinal therapy.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with no cure and limited treatment options. Recent studies have shown that delivering cellular therapeutics to the ventral horn of the spinal cord can effectively halt neurodegeneration associated with ALS in small animal models. METHODS: We developed a robotic system that assists with MRI-guided percutaneous injections to the spinal cord. The needle positioning robot consists of two linear axes with motorised translational sleds for two-degree-of-freedom (2-DOF) needle translation and a radial template for 2-DOF discrete rotation. RESULTS: The robot's targeting capability, evaluated using phantom models and swine cadavers, showed mean targeting errors of 0.48 and 2.84 mm, respectively. The duration of the targeting procedure is approximately 60 min, with an extra 10 min for each additional injection. CONCLUSIONS: The presented robot does not affect imaging quality during MRI-guided procedures, and it enables a simplified workflow for MRI-guided spinal therapy.

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.