Objectives: The objective of this study was to compare the relative impact of two simulation-based methods for training emergency medicine (EM) residents in disaster triage using the Simple Triage and Rapid Treatment (START) algorithm, full-immersion virtual reality (VR), and standardized patient (SP) drill. Specifically, are there differences between the triage performances and posttest results of the two groups, and do both methods differentiate between learners of variable experience levels?Methods: Fifteen Postgraduate Year 1 (PGY1) to PGY4 EM residents were randomly assigned to two groups: VR or SP. In the VR group, the learners were effectively surrounded by a virtual mass disaster environment projected on four walls, ceiling, and floor and performed triage by interacting with virtual patients in avatar form. The second group performed likewise in a live disaster drill using SP victims. Setting and patient presentations were identical between the two modalities. Resident performance of triage during the drills and knowledge of the START triage algorithm pre ⁄ post drill completion were assessed. Analyses included descriptive statistics and measures of association (effect size).Results: The mean pretest scores were similar between the SP and VR groups. There were no significant differences between the triage performances of the VR and SP groups, but the data showed an effect in favor of the SP group performance on the posttest. Conclusions:Virtual reality can provide a feasible alternative for training EM personnel in mass disaster triage, comparing favorably to SP drills. Virtual reality provides flexible, consistent, on-demand training options, using a stable, repeatable platform essential for the development of assessment protocols and performance standards. ACADEMIC EMERGENCY MEDICINE 2010; 17:870-876 ª 2010 by the Society for Academic Emergency MedicineKeywords: disaster medicine, mass casualty incidents, triage D isasters are inevitable, and when they occur, emergency medicine (EM) personnel must be able to respond rapidly and accurately. Preparing EM personnel for disasters is difficult because of the variability in the types of disasters and their locations; the emotional and physical stresses encountered when working in a potentially unstable or dangerous environment with many injured, disoriented, and panicking people; the limited available information about the victims for medical providers; and the challenges of providing training context to master and maintain infrequently required, but critical skills. Research in disaster medicine suggests that although no training can absolutely prepare EM clinicians to perform triage for a true mass casualty incident, familiarity with the process helps rescuer efficiency and comfort in performing triage tasks.

Background For many years, clinicians have been seeking for objective pain assessment solutions via neuroimaging techniques, focusing on the brain to detect human pain. Unfortunately, most of those techniques are not applicable in the clinical environment or lack accuracy. Objective This study aimed to test the feasibility of a mobile neuroimaging-based clinical augmented reality (AR) and artificial intelligence (AI) framework, CLARAi, for objective pain detection and also localization direct from the patient’s brain in real time. Methods Clinical dental pain was triggered in 21 patients by hypersensitive tooth stimulation with 20 consecutive descending cold stimulations (32°C-0°C). We used a portable optical neuroimaging technology, functional near-infrared spectroscopy, to gauge their cortical activity during evoked acute clinical pain. The data were decoded using a neural network (NN)–based AI algorithm to classify hemodynamic response data into pain and no-pain brain states in real time. We tested the performance of several networks (NN with 7 layers, 6 layers, 5 layers, 3 layers, recurrent NN, and long short-term memory network) upon reorganized data features on pain diction and localization in a simulated real-time environment. In addition, we also tested the feasibility of transmitting the neuroimaging data to an AR device, HoloLens, in the same simulated environment, allowing visualization of the ongoing cortical activity on a 3-dimensional brain template virtually plotted on the patients’ head during clinical consult. Results The artificial neutral network (3-layer NN) achieved an optimal classification accuracy at 80.37% (126,000/156,680) for pain and no pain discrimination, with positive likelihood ratio (PLR) at 2.35. We further explored a 3-class localization task of left/right side pain and no-pain states, and convolutional NN-6 (6-layer NN) achieved highest classification accuracy at 74.23% (1040/1401) with PLR at 2.02. Conclusions Additional studies are needed to optimize and validate our prototype CLARAi framework for other pains and neurologic disorders. However, we presented an innovative and feasible neuroimaging-based AR/AI concept that can potentially transform the human brain into an objective target to visualize and precisely measure and localize pain in real time where it is most needed: in the doctor’s office. International Registered Report Identifier (IRRID) RR1-10.2196/13594

Magnetic resonance imaging (MRI) is an extremely useful tool for the detection and characterization of numerous pathologic processes. Although patients can benefit from the use of MRI, claustrophobia is a major issue in some cases. This fear alone can lead to cancellation of the scanning procedure in some cases and the need for conscious sedation in others. Patient anxiety during the scan can also lead to increased motion-related artifacts on the images with associated degradation of the diagnostic quality of the study. To alleviate these problems, our team developed a virtual reality (VR) tool (app) to educate patients about MRI and simulate the experience of actually being scanned. The app is totally immersive and incorporates both the visual and auditory sensations that patients encounter during an MRI scan. Patients also learn about potential conditions and implanted devices that may preclude the safe performance of the examination. This VR tool not only educates patients about MRI and its importance in their care, but also allows them to virtually experience what it is like to have a MRI scan. This technology has the potential to decrease both claustrophobic cancellations and patient anxiety before a MRI scan.

Background Pain is a complex experience that involves sensory-discriminative and cognitive-emotional neuronal processes. It has long been known across cultures that pain can be relieved by mindful breathing (MB). There is a common assumption that MB exerts its analgesic effect through interoception. Interoception refers to consciously refocusing the mind’s attention to the physical sensation of internal organ function. Objective In this study, we dissect the cortical analgesic processes by imaging the brains of healthy subjects exposed to traditional MB (TMB) and compare them with another group for which we augmented MB to an outside sensory experience via virtual reality breathing (VRB). Methods The VRB protocol involved in-house–developed virtual reality 3D lungs that synchronized with the participants’ breathing cycles in real time, providing them with an immersive visual-auditory exteroception of their breathing. Results We found that both breathing interventions led to a significant increase in pain thresholds after week-long practices, as measured by a thermal quantitative sensory test. However, the underlying analgesic brain mechanisms were opposite, as revealed by functional near-infrared spectroscopy data. In the TMB practice, the anterior prefrontal cortex uniquely modulated the premotor cortex. This increased its functional connection with the primary somatosensory cortex (S1), thereby facilitating the S1-based sensory-interoceptive processing of breathing but inhibiting its other role in sensory-discriminative pain processing. In contrast, virtual reality induced an immersive 3D exteroception with augmented visual-auditory cortical activations, which diminished the functional connection with the S1 and consequently weakened the pain processing function of the S1. Conclusions In summary, our study suggested two analgesic neuromechanisms of VRB and TMB practices—exteroception and interoception—that distinctively modulated the S1 processing of the ascending noxious inputs. This is in line with the concept of dualism (Yin and Yang).