Feasibility Assessment of a Pre-Hospital Automated Sensing Clinical Documentation System.

Clinical documentation in the pre-hospital setting is challenged by limited resources and fast-paced, high-acuity. Military and civilian medics are responsible for performing procedures and treatments to stabilize the patient, while transporting the injured to a trauma facility. Upon arrival, medics typically give a verbal report from memory or informal source of documentation such as a glove or piece of tape. The development of an automated documentation system would increase the accuracy and amount of information that is relayed to the receiving physicians. This paper discusses the 12-week deployment of an Automated Sensing Clinical Documentation (ASCD) system among the Nashville Fire Department EMS paramedics. The paper examines the data collection methods, operational challenges, and perceptions surrounding real-life deployment of the system. Our preliminary results suggest that the ASCD system is feasible for use in the pre-hospital setting, and it revealed several barriers and their solutions.

Validating an objective video-based dyskinesia severity score in Parkinson's disease patients.

Dyskinesia is a common side effect of prolonged dopaminergic therapy in Parkinson's disease patients. Assessing the severity of dyskinesia could help develop better pharmacological and surgical interventions. We have developed a semi-automatic video-based objective dyskinesia quantifying measure called the severity score (SVS) that was evaluated on 35 patient videos. We present a study to evaluate the utility of our severity score and compare its performance to clinical ratings of neurologists. In addition to the Unified Dyskinesia Rating Scale (UDysRS) score for each video, four neurologists provided three sets of time lapsed ratings and rankings of the 35 videos using a specifically developed protocol. The statistical analysis of our data using Kendall's tau-b and intra-class correlations shows that (a) ranking patient videos based on severity is suitable for studying the utility of the SVS, and (b) SVS exhibits moderate utility to quantify dyskinesia severity when compared to manual assessment of dyskinesia by neurologists using the UDysRS. These results support the effective use of SVS as an objective measure to quantify dyskinesia and the rationale for a ranking system that complements traditional rating scales.

Immersive Virtual Reality for Visualization of Abdominal CT.

Immersive virtual environments use a stereoscopic head-mounted display and data glove to create high fidelity virtual experiences in which users can interact with three-dimensional models and perceive relationships at their true scale. This stands in stark contrast to traditional PACS-based infrastructure in which images are viewed as stacks of two-dimensional slices, or, at best, disembodied renderings. Although there has substantial innovation in immersive virtual environments for entertainment and consumer media, these technologies have not been widely applied in clinical applications. Here, we consider potential applications of immersive virtual environments for ventral hernia patients with abdominal computed tomography imaging data. Nearly a half million ventral hernias occur in the United States each year, and hernia repair is the most commonly performed general surgery operation worldwide. A significant problem in these conditions is communicating the urgency, degree of severity, and impact of a hernia (and potential repair) on patient quality of life. Hernias are defined by ruptures in the abdominal wall (i.e., the absence of healthy tissues) rather than a growth (e.g., cancer); therefore, understanding a hernia necessitates understanding the entire abdomen. Our environment allows surgeons and patients to view body scans at scale and interact with these virtual models using a data glove. This visualization and interaction allows users to perceive the relationship between physical structures and medical imaging data. The system provides close integration of PACS-based CT data with immersive virtual environments and creates opportunities to study and optimize interfaces for patient communication, operative planning, and medical education.

Quantifying drug induced dyskinesia in Parkinson's disease patients using standardized videos.

This paper presents a video based method to quantify drug induced dyskinesias in Parkinson's disease (PD) patients. Dyskinetic movement in standard clinical videos of patients is analyzed by tracking landmark points on the video frames using non-rigid image registration. The novel application of Point Distribution Models (PDM) allows geometric variations and covariations of the landmark points to be captured from each video sequence. The PDM parameters represent quantifiable information that can be used to rate dyskinesia effectively, analogously to a neurologist's strategy of assessing the movement of multiple body parts simultaneously to effectively rate dyskinesia. A heuristic decision function is then developed using the PDM parameters to quantify the severity of the dyskinesia. The severity score using our decision function showed a high correlation to the dyskinesia rating of a neurologist on the corresponding patient videos.