Drugs and the gastrointestinal tract

16.1. Agents to control acidity 16.1.1 Antacids 16.1.2 Proton pump inhibitors and antibiotics for Helicobacter pylori 16.1.3 Histamine H2 receptor antagonists 16.1.4 Misoprostol 16.1.5 Sucralfate 16.2. Prokinetics and emetics 16.2.1 Introduction to prokinetics 16.2.2 Prokinetic agents 16.2.3 Emesis with cytotoxic drugs and drugs for 16.2.4 Motion sickness and drugs for 16.2.5 Drugs for post-operative emesis 16.3. Agents used for diarrhea, constipation, irritable bowel syndrome 16.3.1 Treatment for diarrhea 16.3.2 Treatment for constipation 16.3.3 Treatment for opioid-induced constipation 16.4. Drugs for inflammatory bowel disease 16.4.1 Mesalazine 16.4.2 Glucocorticoids 16.4.3 Infliximab

Assessment of driving-related performance in chronic whiplash using an advanced driving simulator

Driving is often nominated as problematic by individuals with chronic whiplash associated disorders (WAD), yet driving-related performance has not been evaluated objectively. The purpose of this study was to test driving-related performance in persons with chronic WAD against healthy controls of similar age, gender and driving experience to determine if driving-related performance in the WAD group was sufficiently impaired to recommend fitness to drive assessment. Driving-related performance was assessed using an advanced driving simulator during three driving scenarios; freeway, residential and a central business district (CBD). Total driving duration was approximately 15 min. Five driving tasks which could cause a collision (critical events) were included in the scenarios. In addition, the effect of divided attention (identify red dots projected onto side or rear view mirrors) was assessed three times in each scenario. Driving performance was measured using the simulator performance index (SPI) which is calculated from 12 measures. z-Scores for all SPI measures were calculated for each WAD subject based on mean values of the control subjects. The z-scores were then averaged for the WAD group. A z-score of ≤−2 indicated a driving failing grade in the simulator. The number of collisions over the five critical events was compared between the WAD and control groups as was reaction time and missed response ratio in identifying the red dots. Seventeen WAD and 26 control subjects commenced the driving assessment. Demographic data were comparable between the groups. All subjects completed the freeway scenario but four withdrew during the residential and eight during the CBD scenario because of motion sickness. All scenarios were completed by 14 WAD and 17 control subjects. Mean z-scores for the SPI over the three scenarios was statistically lower in the WAD group (−0.3 ± 0.3; P < 0.05) but the score was not below the cut-off point for safe driving. There were no differences in the reaction time and missed response ratio in divided attention tasks between the groups (All P > 0.05). Assessment of driving in an advanced driving simulator for approximately 15 min revealed that driving-related performance in chronic WAD was not sufficiently impaired to recommend the need for fitness to drive assessment.

Person tracking using motion detection and optical flow

Person tracking systems to date have either relied on motion detection or optical flow as a basis for person detection and tracking. As yet, systems have not been developed that utilise both these techniques. We propose a person tracking system that uses both, made possible by a novel hybrid optical flow-motion detection technique that we have developed. This provides the system with two methods of person detection, helping to avoid missed detections and the need to predict position, which can lead to errors in tracking and mistakes when handling occlusion situations. Our results show that our system is able to track people accurately, with an average error less than four pixels, and that our system outperforms the current CAVIAR benchmark system.

Constraints on the complete optimization of human motion

In sport and exercise biomechanics, forward dynamics analyses or simulations have frequently been used in attempts to establish optimal techniques for performance of a wide range of motor activities. However, the accuracy and validity of these simulations is largely dependent on the complexity of the mathematical model used to represent the neuromusculoskeletal system. It could be argued that complex mathematical models are superior to simple mathematical models as they enable basic mechanical insights to be made and individual-specific optimal movement solutions to be identified. Contrary to some claims in the literature, however, we suggest that it is currently not possible to identify the complete optimal solution for a given motor activity. For a complete optimization of human motion, dynamical systems theory implies that mathematical models must incorporate a much wider range of organismic, environmental and task constraints. These ideas encapsulate why sports medicine specialists need to adopt more individualized clinical assessment procedures in interpreting why performers' movement patterns may differ.

Seeing pedestrians at night : visual clutter does not mask biological motion

Although placing reflective markers on pedestrians’ major joints can make pedestrians more conspicuous to drivers at night, it has been suggested that this “biological motion” effect may be reduced when visual clutter is present. We tested whether extraneous points of light affected the ability of 12 younger and 12 older drivers to see pedestrians as they drove on a closed road at night. Pedestrians wore black clothing alone or with retroreflective markings in four different configurations. One pedestrian walked in place and was surrounded by clutter on half of the trials. Another was always surrounded by visual clutter but either walked in place or stood still. Clothing configuration, pedestrian motion, and driver age influenced conspicuity but clutter did not. The results confirm that even in the presence of visual clutter pedestrians wearing biological motion configurations are recognized more often and at greater distances than when they wear a reflective vest.

A brush with the real world : the future of inertial motion capture in live performance

3D Motion capture is a medium that plots motion, typically human motion, converting it into a form that can be represented digitally. It is a fast evolving field and recent inertial technology may provide new artistic possibilities for its use in live performance. Although not often used in this context, motion capture has a combination of attributes that can provide unique forms of collaboration with performance arts. The inertial motion capture suit used for this study has orientation sensors placed at strategic points on the body to map body motion. Its portability, real-time performance, ease of use, and its immunity from line-of-sight problems inherent in optical systems suggest it would work well as a live performance technology. Many animation techniques can be used in real-time. This research examines a broad cross-section of these techniques using four practice-led cases to assess the suitability of inertial motion capture to live performance. Although each case explores different visual possibilities, all make use of the performativity of the medium, using either an improvisational format or interactivity among stage, audience and screen that would be difficult to emulate any other way. A real-time environment is not capable of reproducing the depth and sophistication of animation people have come to expect through media. These environments take many hours to render. In time the combination of what can be produced in real-time and the tools available in a 3D environment will no doubt create their own tree of aesthetic directions in live performance. The case study looks at the potential of interactivity that this technology offers.

Abandoned object detection using multi-layer motion detection

Abandoned object detection (AOD) systems are required to run in high traffic situations, with high levels of occlusion. Systems rely on background segmentation techniques to locate abandoned objects, by detecting areas of motion that have stopped. This is often achieved by using a medium term motion detection routine to detect long term changes in the background. When AOD systems are integrated into person tracking system, this often results in two separate motion detectors being used to handle the different requirements. We propose a motion detection system that is capable of detecting medium term motion as well as regular motion. Multiple layers of medium term (static) motion can be detected and segmented. We demonstrate the performance of this motion detection system and as part of an abandoned object detection system.