Recent articles support the hypothesis that VR therapies can effectively distract patients who suffer from chronic pain and from acute pain stimulated in trials. Clinical studies yield promising results in the application of VR therapies to a variety of acute and chronic pain conditions, including fibromyalgia, phantom limb pain, and regional specific pain from past injuries and illnesses. Current management techniques for acute and chronic pain, such as opioids and physical therapy, are often incomplete or ineffective. VR trials demonstrate a potential to redefine the approach to treating acute and chronic pain in the clinical setting. Patient immersion in interactive virtual reality provides distraction from painful stimuli and can decrease an individual's perception of the pain. In this review, we discuss the use of VR to provide patient distraction from acute pain induced from electrical, thermal, and pressure conditions. We also discuss the application of VR technologies to treat various chronic pain conditions in both outpatient and inpatient settings.

Mechanical biomarkers associated with cytoskeletal structures have been reported as powerful label-free cell state identifiers. In order to measure cell mechanical properties, traditional biophysical (e.g., atomic force microscopy, micropipette aspiration, optical stretchers) and microfluidic approaches were mainly employed; however, they critically suffer from low-throughput, low-sensitivity, and/or time-consuming and labor-intensive processes, not allowing techniques to be practically used for cell biology research applications. Here, a novel inertial microfluidic cell stretcher (iMCS) capable of characterizing large populations of single-cell deformability near real-time is presented. The platform inertially controls cell positions in microchannels and deforms cells upon collision at a T-junction with large strain. The cell elongation motions are recorded, and thousands of cell deformability information is visualized near real-time similar to traditional flow cytometry. With a full automation, the entire cell mechanotyping process runs without any human intervention, realizing a user friendly and robust operation. Through iMCS, distinct cell stiffness changes in breast cancer progression and epithelial mesenchymal transition are reported, and the use of the platform for rapid cancer drug discovery is shown as well. The platform returns large populations of single-cell quantitative mechanical properties (e.g., shear modulus) on-the-fly with high statistical significances, enabling actual usages in clinical and biophysical studies.

Through computer-generated, life-like digital landscapes, VR stands to change the current approach to pain management, medical training, neurocognitive diagnosis, and physical rehabilitation. Additional studies are needed to help define best practices in VR utilization, and to explore new therapeutic uses for VR in clinical practice.

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IntroductionAsynchronous online training has become an increasingly popular educational format in the new era of technology-based professional development. We sought to evaluate the impact of an online asynchronous training module on the ability of medical students and emergency medicine (EM) residents to detect electrocardiogram (ECG) abnormalities of an acute myocardial infarction (AMI).MethodsWe developed an online ECG training and testing module on AMI, with emphasis on recognizing ST elevation myocardial infarction (MI) and early activation of cardiac catheterization resources. Study participants included senior medical students and EM residents at all post-graduate levels rotating in our emergency department (ED). Participants were given a baseline set of ECGs for interpretation. This was followed by a brief interactive online training module on normal ECGs as well as abnormal ECGs representing an acute MI. Participants then underwent a post-test with a set of ECGs in which they had to interpret and decide appropriate intervention including catheterization lab activation.Results148 students and 35 EM residents participated in this training in the 2012–2013 academic year. Students and EM residents showed significant improvements in recognizing ECG abnormalities after taking the asynchronous online training module. The mean score on the testing module for students improved from 5.9 (95% CI [5.7–6.1]) to 7.3 (95% CI [7.1–7.5]), with a mean difference of 1.4 (95% CI [1.12–1.68]) (p<0.0001). The mean score for residents improved significantly from 6.5 (95% CI [6.2–6.9]) to 7.8 (95% CI [7.4–8.2]) (p<0.0001).ConclusionAn online interactive module of training improved the ability of medical students and EM residents to correctly recognize the ECG evidence of an acute MI.