Novel patterns of visual-vestibular intersensory stimulation often result in symptoms of simulator sickness, raising health and safety concerns regarding virtual environment exposure. Two experiments investigated the effect of conflicting visual-vestibular cues on subjective reports of simulator sickness during and after a 50-min exposure to a head-coupled virtual interface. Virtual image scale factors (0.5. 1.0, 2.0 magnification, generated by varying geometric field of view angle) were investigated in Experiment 1, and additional system time delays (125, 250 ms) were investigated in Experiment 2. Simulator sickness metrics included spoken self-reports during exposure and simulator sickness questionnaires (pre-exposure, immediate postexposure, and 20 min postexposure). Head yaw angular position data were also recorded. Reports of simulator sickness symptoms were significantly greater in the minification (0.5) and magnification (2.0) image scale factor conditions than in the neutral condition (1.0). Simulator sickness did not vary with changes in time delay, however. Furthermore, a comparison across experiments suggests no appreciable increase in simulator sickness with increasing time delays above the nominal value (48 ms). Head angular position data exhibited certain systematic variations across conditions. Actual or potential applications of this research include virtual environment training, simulation, and entertainment systems.

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The goal of human factors engineering is to optimize the relationship between humans and systems by studying human behavior, abilities, and limitations and using this knowledge to design systems for safe and effective human use. With the assumption that the human component of any system will inevitably produce errors, human factors engineers design systems and human/machine interfaces that are robust enough to reduce error rates and the effect of the inevitable error within the system. In this article, we review the extent and nature of medical error and then discuss human factors engineering tools that have potential applicability. These tools include taxonomies of human and system error and error data collection and analysis methods. Finally, we describe studies that have examined medical error, and on the basis of these studies, present conclusions about how human factors engineering can significantly reduce medical errors and their effects.

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