Virtual reality and a haptic master-slave set-up in post-stroke upper-limb rehabilitation.

Since the number of stroke patients is ever growing, and since studies show that the patients can benefit from more exercise, the possible use of virtual reality and haptic devices in the rehabilitation of stroke patients is researched. Besides offering more independent and challenging exercise possibilities, the inherent registration capabilities of the haptic devices open up the possibility of monitoring patients' motions in an objective way. This research results in the implementation of a VR mock-up of an exercise in which patients use both hands and a stick to push away a ball that is tossed at them.

Open surgery in VR: inguinal hernia repair according to Lichtenstein.

VREST (Virtual Reality Educational Surgical Tools) is developing a universal and autonomous simulation platform which can be used for training and assessment of medical students and for continuing education of physicians. A workstation consisting of two haptic devices and a 3D vision system is part of the VREST platform. Another part of the platform is a generic software environment in which lessons can be built by the teacher and performed by their students.

The effects of a specific prompting sign on speed reduction.

The purpose of this experiment was to determine whether a specifically worded prompting sign ("BEGIN SLOWING HERE") could reduce speeding where a highway entered an urban area with a residential speed limit. Speed measurements were obtained on vehicles at the start of the residential speed limit zone. Following a baseline period the prompting sign was introduced, removed and reintroduced.

Excretory urography in current practice: evidence against overutilization.

Excretory urography could be performed less frequently if some combinations of genitourinary signs and symptoms were found to be predictive of either a specific disease or normality. To explore this possibility, the authors conducted a prospective study involving more than 3,000 patients at three institutions (a teaching hospital, a community hospital, and a health maintenance organization). Predictive algorithms were obtained by application of a polychotomous logistic regression model but did poorly at differentiating normal from abnormal patients or arriving at a specific diagnosis.