The use of kernel density estimation to examine associations between neighborhood destination intensity and walking and physical activity

BACKGROUND: Local destinations have previously been shown to be associated with higher levels of both physical activity and walking, but little is known about how the distribution of destinations is related to activity. Kernel density estimation is a spatial analysis technique that accounts for the location of features relative to each other. Using kernel density estimation, this study sought to investigate whether individuals who live near destinations (shops and service facilities) that are more intensely distributed rather than dispersed: 1) have higher odds of being sufficiently active; 2) engage in more frequent walking for transport and recreation. METHODS: The sample consisted of 2349 residents of 50 urban areas in metropolitan Melbourne, Australia. Destinations within these areas were geocoded and kernel density estimates of destination intensity were created using kernels of 400m (meters), 800m and 1200m. Using multilevel logistic regression, the association between destination intensity (classified in quintiles Q1(least)-Q5(most)) and likelihood of: 1) being sufficiently active (compared to insufficiently active); 2) walking≥4/week (at least 4 times per week, compared to walking less), was estimated in models that were adjusted for potential confounders. RESULTS: For all kernel distances, there was a significantly greater likelihood of walking≥4/week, among respondents living in areas of greatest destinations intensity compared to areas with least destination intensity: 400m (Q4 OR 1.41 95%CI 1.02-1.96; Q5 OR 1.49 95%CI 1.06-2.09), 800m (Q4 OR 1.55, 95%CI 1.09-2.21; Q5, OR 1.71, 95%CI 1.18-2.48) and 1200m (Q4, OR 1.7, 95%CI 1.18-2.45; Q5, OR 1.86 95%CI 1.28-2.71). There was also evidence of associations between destination intensity and sufficient physical activity, however these associations were markedly attenuated when walking was included in the models. CONCLUSIONS: This study, conducted within urban Melbourne, found that those who lived in areas of greater destination intensity walked more frequently, and showed higher odds of being sufficiently physically active-an effect that was largely explained by levels of walking. The results suggest that increasing the intensity of destinations in areas where they are more dispersed; and or planning neighborhoods with greater destination intensity, may increase residents' likelihood of being sufficiently active for health.

Haptic virtual reality training environment for micro-robotic cell injection

Micro-robotic cell injection is typically performed manually by a trainedbio-operator, and success rates are often low. To enhance bio-operator performance during real-time cell injection, our earlier work introduced a haptically-enabled micro-robotic cell injection system. The system employed haptic virtual fixtures to provide haptic guidance according to articular performance metrics. This paper extends the work by replicating the system within a virtual reality (VR) environment for bio-operator training. Using the virtual environment, the bio-operator is able to control the virtual injection process in the same way they would with the physical haptic micro-robotic cell injection system, while benefiting from the enhanced visualisation capabilities offered by the 3D VR environment. The system is achieved using cost-effective components offering training at much lower cost than using the physical system.

Building the computational virtual reality environment for anaesthetists' training and practice

Understanding the real world based on visualisation and prediction is essential for the decision-maker. We build a computational virtual reality environment to improve visualisation, understanding and prediction of the physical world and to guide action. It develops a five-dimensional, computer-generated, computational Virtual Reality Environment for Anaesthesia (VREA). Our online prediction will be calculated based on the correlation and composition computing with respect to the three dimensions: horizontal, vertical and individual. The novel musical notes based anesthetic simulator is proposed to identify the abnormality and visualize the online medical time series. The experiments with the online ECG data will present a real-time case to show the effectiveness and efficiency of our proposed system and algorithms.