Who's Better? Who's Best? Pairwise Deep Ranking for Skill Determination

We present a method for assessing skill from video, applicable to a variety of tasks, ranging from surgery to drawing and rolling pizza dough. We formulate the problem as pairwise (who's better?) and overall (who's best?) ranking of video collections, using supervised deep ranking. We propose a novel loss function that learns discriminative features when a pair of videos exhibit variance in skill, and learns shared features when a pair of videos exhibit comparable skill levels. Results demonstrate our method is applicable across tasks, with the percentage of correctly ordered pairs of videos ranging from 70% to 83% for four datasets. We demonstrate the robustness of our approach via sensitivity analysis of its parameters. We see this work as effort toward the automated organization of how-to video collections and overall, generic skill determination in video.Comment: CVPR 201

Using Peripheral Venous Pressure Waveforms to Predict Key Hemodynamic Parameters

Analysis of peripheral venous pressure (PVP) waveforms is a novel method of monitoring intravascular volume. Two cohorts were used to study the hemodynamics change of the body state and its influence on the PVP using (1) dehydration setting with infants suffering from pyloric stenosis and (2) hemorrhage setting during a craniosynostosis elective surgery. The goal of this research is to develop a minimally invasive method of analyzing the PVP waveforms and find correlations with volume loss. Twenty-three pyloric stenosis patients PVP were acquired at five stages and were divided into euvolemic, normal fluid volume, and hypovolemic, significant fluid loss. Seven craniosynostosis patients were enrolled and the PVP was acquired at the intervention to explore if the isoflurane dosage influences the PVP. A multivariate analysis of variances (MANOVA) was used to test if the PVP was influenced by the volume change and the anesthetic drugs effect. Prediction algorithms based on Fast Fourier Transform were utilized at the two cohort patients analyses to classify an arbitrary PVP into its correct classification. Our research found that PVP signal is influenced by the different hemodynamics states of the body. Based on MANOVA outcomes, we built prediction systems and they were able to categorize an arbitrary PVP signal into its correct classification. The k-nearest neighbor (k-NN) model correctly predicted 77% of the data in the euvolemic and hypovolemic groups. The k-NN models of the anesthetic drugs were able to correctly predict correctly at least 85% of the preoperative and intraoperative signals of the pyloric stenosis patients and the different isoflurane dosages of the craniosynostosis patients. Analyzing the PVP signal is a promising tool for measuring the dehydration level in acute settings. Our results imply that the subsequent changes in vascular resistance due to inhaled and infused anesthetics are reflected in the peripheral veins. A technology that would accurately assess the volume status of a patient to guide triage and treatment would be a significant improvement in various care settings. This minimally invasive technology utilizes a standard peripheral intravenous line and a commercial pressure-monitoring transducer, which exist today and requires no new clinical skills

Opportunities for improving animal welfare in rodent models of epilepsy and seizures

Animal models of epilepsy and seizures, mostly involving mice and rats, are used to understand the pathophysiology of the different forms of epilepsy and their comorbidities, to identify biomarkers, and to discover new antiepileptic drugs and treatments for comorbidities. Such models represent an important area for application of the 3Rs (replacement, reduction and refinement of animal use). This report provides background information and recommendations aimed at minimising pain, suffering and distress in rodent models of epilepsy and seizures in order to improve animal welfare and optimise the quality of studies in this area. The report includes practical guidance on principles of choosing a model, induction procedures, in vivo recordings, perioperative care, welfare assessment, humane endpoints, social housing, environmental enrichment, reporting of studies and data sharing. In addition, some model-specific welfare considerations are discussed, and data gaps and areas for further research are identified. The guidance is based upon a systematic review of the scientific literature, survey of the international epilepsy research community, consultation with veterinarians and animal care and welfare officers, and the expert opinion and practical experience of the members of a Working Group convened by the United Kingdom's National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs)