Deep understanding of shopper behaviours and interactions using RGB-D vision

AbstractIn retail environments, understanding how shoppers move about in a store's spaces and interact with products is very valuable. While the retail environment has several favourable characteristics that support computer vision, such as reasonable lighting, the large number and diversity of products sold, as well as the potential ambiguity of shoppers' movements, mean that accurately measuring shopper behaviour is still challenging. Over the past years, machine-learning and feature-based tools for people counting as well as interactions analytic and re-identification were developed with the aim of learning shopper skills based on occlusion-free RGB-D cameras in a top-view configuration. However, after moving into the era of multimedia big data, machine-learning approaches evolved into deep learning approaches, which are a more powerful and efficient way of dealing with the complexities of human behaviour. In this paper, a novel VRAI deep learning application that uses three convolutional neural networks to count the number of people passing or stopping in the camera area, perform top-view re-identification and measure shopper–shelf interactions from a single RGB-D video flow with near real-time performances has been introduced. The framework is evaluated on the following three new datasets that are publicly available: TVHeads for people counting, HaDa for shopper–shelf interactions and TVPR2 for people re-identification. The experimental results show that the proposed methods significantly outperform all competitive state-of-the-art methods (accuracy of 99.5% on people counting, 92.6% on interaction classification and 74.5% on re-id), bringing to different and significative insights for implicit and extensive shopper behaviour analysis for marketing applications

Geriatric pharmacotherapy : optimisation through integrated approach in the hospital setting

Since older patients are more vulnerable to adverse drug-related events, there is a need to ensure appropriate prescribing in these patients in order to prevent misuse, overuse and underuse of drugs. Different tools and strategies have been developed to reduce inappropriate prescribing; the available measures can be divided into medication assessment tools, and specific interventions to reduce inappropriate prescribing. Implicit criteria of inappropriate prescribing focus on appropriate dosing, search for drug-drug interactions, and increase adherence. Explicit criteria are consensus-based standards focusing on drugs and diseases and include lists of drugs to avoid in general or lists combining drugs with clinical data. These criteria take into consideration differences between patients, and stand for a medication review, by using a systematic approach. Different types of interventions exist in order to reduce inappropriate prescribing in older patients, such as: educational interventions, computerized decision support systems, pharmacist-based interventions, and geriatric assessment. The effects of these interventions have been studied, sometimes in a multifaceted approach combining different techniques, and all types seem to have positive effects on appropriateness of prescribing. Interdisciplinary teamwork within the integrative pharmaceutical care is important for improving of outcomes and safety of drug therapy. The pharmaceutical care process consists offour steps, which are cyclic for an individual patient. These steps are pharmaceutical anamnesis, medication review, design and follow-up of a pharmaceutical care plan. A standardized approach is necessary for the adequate detection and evaluation of drug-related problems. Furthermore, it is clear that drug therapy should be reviewed in-depth, by having full access to medical records, laboratory values and nursing notes. Although clinical pharmacists perform the pharmaceutical care process to manage the patient’s drug therapy in every day clinical practice, the physician takes the ultimate responsibility for the care of the patient in close collaboration with nurses

Surveying Persons with Disabilities: A Source Guide (Version 1)

As a collaborator with the Cornell Rehabilitation Research and Training Center on Disability Demographics and Statistics, Mathematica Policy Research, Inc. has been working on a project that identifies the strengths and limitations in existing disability data collection in both content and data collection methodology. The intended outcomes of this project include expanding and synthesizing knowledge of best practices and the extent existing data use those practices, informing the development of data enhancement options, and contributing to a more informed use of existing data. In an effort to provide the public with an up-to-date and easily accessible source of research on the methodological issues associated with surveying persons with disabilities, MPR has prepared a Source Guide of material related to this topic. The Source Guide contains 150 abstracts, summaries, and references, followed by a Subject Index, which cross references the sources from the Reference List under various subjects. The Source Guide is viewed as a “living document,” and will be periodically updated

Design and Implementation of Cardiopulmonary Resuscitation Simulation Model

Cardiopulmonary resuscitation (CPR) is a life-saving procedure that can multiply a person's chances of survival after a cardiac arrest. The effectiveness of CPR procedures is heavily influenced by the individual skills of the rescuer providing assistance. Chest compressions delivered at an appropriate depth and rate, allowing full chest recoil and with minimal interruptions, are critical for improving cardiac arrest survival. The lack of quality CPR training models in developing countries has a significant impact on the quality of CPR training and skills acquired. Therefore, in this paper, we aim at improving CPR training by designing a high-fidelity CPR training manikin. The model includes a feedback mechanism for monitoring CPR performance status to allow for effective practice and rehearsal until required CPR skills are acquired. An in-depth study of existing training systems was conducted to ensure the proper design of the proposed system. The test results show that the designed manikin prototype analyses the quality of CPR performance and provides appropriate feedback to the trainee. The model can be used for training medical students and other practitioners to correctly perform CPR