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

Deep reinforcement learning for soft, flexible robots : brief review with impending challenges

The increasing trend of studying the innate softness of robotic structures and amalgamating it with the benefits of the extensive developments in the field of embodied intelligence has led to the sprouting of a relatively new yet rewarding sphere of technology in intelligent soft robotics. The fusion of deep reinforcement algorithms with soft bio-inspired structures positively directs to a fruitful prospect of designing completely self-sufficient agents that are capable of learning from observations collected from their environment. For soft robotic structures possessing countless degrees of freedom, it is at times not convenient to formulate mathematical models necessary for training a deep reinforcement learning (DRL) agent. Deploying current imitation learning algorithms on soft robotic systems has provided competent results. This review article posits an overview of various such algorithms along with instances of being applied to real-world scenarios, yielding frontier results. Brief descriptions highlight the various pristine branches of DRL research in soft robotics

Magnetic resonance conditional microinjector

Glaucoma, one of the leading causes of blindness, has been linked to increases in intraocular pressure. In order to observe and study this effect, proposed is a specialized microinjector and driver that can be used to inject small amounts of liquid into a target volume. Magnetic resonance imaging (MRI) guided remotely activated devices require specialized equipment that is compatible with the MR environment. This paper presents an MR Conditional microinjector system with a pressure sensor for investigating the effects of intraocular pressure (IOP) in near-real-time. The system uses pressurized air and a linear actuation device to push a syringe in a controlled, stepwise manner. The feasibility and utility of the proposed investigative medical research tool were tested and validated by measuring the pressure inside an intact animal donor eyeball while precise, small volumes of water were injected into the specimen. Observable increases in the volume of the specimen at measured, specific target pressure increases show that the system is technically feasible for studying IOP effects, while the changes in shape were depicted in MRI scan images themselves. In addition, it was verified that the presence and operation of the system did not interfere with the MRI machine, confirming its conditional compatibility with the 3T MRI

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

Exploring magnetohydrodynamic voltage distributions in the human body : Preliminary results

BACKGROUND: The aim of this study was to noninvasively measure regional contributions of vasculature in the human body using magnetohydrodynamic voltages (VMHD) obtained from electrocardiogram (ECG) recordings performed inside MRI's static magnetic field (B0). Integrating the regional VMHD over the Swave-Twave segment of the cardiac cycle (Vsegment) provides a non-invasive method for measuring regional blood volumes, which can be rapidly obtained during MRI without incurring additional cost. METHODS: VMHD was extracted from 12-lead ECG traces acquired during gradual introduction into a 3T MRI. Regional contributions were computed utilizing weights based on B0's strength at specified distances from isocenter. Vsegment mapping was performed in six subjects and validated against MR angiograms (MRA). RESULTS: Fluctuations in Vsegment, which presented as positive trace deflections, were found to be associated with aortic-arch flow in the thoracic cavity, the main branches of the abdominal aorta, and the bifurcation of the common iliac artery. The largest fluctuation corresponded to the location where the aortic arch was approximately orthogonal to B0. The smallest fluctuations corresponded to areas of vasculature that were parallel to B0. Significant correlations (specifically, Spearman's ranked correlation coefficients of 0.96 and 0.97 for abdominal and thoracic cavities, respectively) were found between the MRA and Vsegment maps (p < 0.001). CONCLUSIONS: A novel non-invasive method to extract regional blood volumes from ECGs was developed and shown to be a rapid means to quantify peripheral and abdominal blood volumes

Applications of Wireless Power Transfer in Medicine : State-of-the-Art Reviews

Magnetic resonance within the field of wireless power transfer has seen an increase in popularity over the past decades. This rise can be attributed to the technological advances of electronics and the increased efficiency of popular battery technologies. The same principles of electromagnetic theory can be applied to the medical field. Several medical devices intended for use inside the body use batteries and electrical circuits that could be powered wirelessly. Other medical devices limit the mobility or make patients uncomfortable while in use. The fundamental theory of electromagnetics can improve the field by solving some of these problems. This survey paper summarizes the recent uses and discoveries of wireless power in the medical field. A comprehensive search for papers was conducted using engineering search engines and included papers from related conferences. During the initial search, 247 papers were found then non-relevant papers were eliminated to leave only suitable material. Seventeen relevant journal papers and/or conference papers were found, then separated into defined categories: Implants, Pumps, Ultrasound Imaging, and Gastrointestinal (GI) Endoscopy. The approach and methods for each paper were analyzed and compared yielding a comprehensive review of these state of the art technologies

Accepted and presented at The Design of Medical Devices Conference (DMD2016)

Magnetic resonance imaging (MRI) is an imaging approach to acquire high-resolution images of soft target tissue particularly for medical applications in both preoperative and intraoperative procedures Unlike electric and electromagnetic actuators, pneumatic motors demonstrate a few advantages. MR-compatible materials, such as plastic, ensure easy fabrication and customized design; the air supply of the pneumatic actuators can be found in most MR rooms; the compressed air does not interface with the MR imaging physics; furthermore, pneumatic actuators can provide little to no signal-to-noise ratio (SNR) reduction in MR images. These advantages result in the fast development of pneumatic actuation for MR-guided robotic interventions The device detailed in this paper is a pneumatic stepper motor. Previous stepper motor designs have generally relied on the intermeshing of different sets of &quot;teeth&quot; to create the rotation and stepwise effect. Chen et al. used a different approach creating a stepper motor composed of two cylinders and a supporting structure The pneumatic stepper motor presented in this paper can rotate 3.6 deg for each step and generate torque up to 918.75 mNÁm. The system setup, motor working principle, and calibration will be discussed in the Methods, and Results sections. Methods The compressed air supply was split into two lines with one line directed to the control box and the other to the switches. Depending on the direction of rotation, a signal was sent to one of two pneumatic valves in the control box to open the pneumatic valve. Then, air flows to the corresponding cylinder, and the cylinder pulls its connected switch to the open position. During a digital low, the pneumatic valve closes and exhausts the air that is trapped in between the valve and cylinder. The supply of air attached to the pneumatic switch flows into the continuous motor. The continuous motor rotates the main axle inside the housing. Attached to the main axle is a cam which flips the currently open switch back to the closed position, stopping air flow to the continuous motor, and causing the motor to slow to a stop. Also, the corresponding cylinder was reset since it is attached to the switch. Essentially, the motor turns itself off. After one rotation of the main shaft, the Geneva drive has advanced by one step. Since the Geneva drive has four slots, each step is equal to 90 deg of rotation. In order to increase the resolution of each step, a second series of planetary gears with a ratio of 25:1 was attached to the output of the Geneva drive resulting i

Statistical properties of seismicity of fault zones at different evolutionary stages

We perform a systematic parameter space study of the seismic response of a large fault with different levels of heterogeneity, using a 3-D elastic framework within the continuum limit. The fault is governed by rate-and-state friction and simulations are performed for model realizations with frictional and large scale properties characterized by different ranges of size scales. We use a number of seismicity and stress functions to characterize different types of seismic responses and test the correlation between hypocenter locations and the employed distributions of model parameters. The simulated hypocenters are found to correlate significantly with small L values of the rate-and-state friction. The final sizes of earthquakes are correlated with physical properties at their nucleation sites. The obtained stacked scaling relations are overall self-similar and have good correspondence with properties of natural earthquakes

Social Media Usage and Influenza Beliefs, Risk Perceptions and Behavioral Intentions Among Students at a University in Southeastern US

Background: To document social media usage for the retrieval of health information among college students; and to understand the beliefs, risk perceptions and behavioral intentions among participants who retrieved CDC influenza information via social media. Methods: We conducted an online survey to a convenience sample of students at a university in Southeastern United States during Spring 2015. The survey was self-administered and every matriculating student received an electronic invitation to participate at least once. Results: A total of 930 students completed the online survey. Most participants (n=905, 97.3%) reported that they had used a social networking site in the previous 12 months. However, only one-third (n=317, 34.1%) reported that they used social networking sites to read CDC health information or messages. Nearly one-fifth of participants (n=172, 18.5%) reported reading CDC influenza information during the 2014-15 influenza season. Among the subset of readers of CDC influenza information during the 2014-15 influenza season (N=153), 77 (50.99%) reported that it was likely they would get the influenza vaccine in the next 12 months. Women reported stronger risk perceptions and behavioral intentions than men. Blacks/African Americans reported more negative influenza-related beliefs and weaker risk perceptions compared to Whites. Conclusions: While social media penetration is high among university students in Southeastern US, only a minority of survey participants retrieved CDC influenza information via social media. Among these individuals, about half reported that they intended to vaccinate against influenza. Further research is needed to enhance CDC social media penetration among college students