Objectives This study shows the development and validation of a dental anesthesia-training simulator, specifically for the inferior alveolar nerve block (IANB). The system developed provides the tactile sensation of inserting a real needle in a human patient, using Virtual Reality (VR) techniques and a haptic device that can provide a perceived force feedback in the needle insertion task during the anesthesia procedure.Material and Methods To simulate a realistic anesthesia procedure, a Carpule syringe was coupled to a haptic device. The Volere method was used to elicit requirements from users in the Dentistry area; Repeated Measures Two-Way ANOVA (Analysis of Variance), Tukey post-hoc test and averages for the results’ analysis. A questionnaire-based subjective evaluation method was applied to collect information about the simulator, and 26 people participated in the experiments (12 beginners, 12 at intermediate level, and 2 experts). The questionnaire included profile, preferences (number of viewpoints, texture of the objects, and haptic device handler), as well as visual (appearance, scale, and position of objects) and haptic aspects (motion space, tactile sensation, and motion reproduction).Results The visual aspect was considered appropriate and the haptic feedback must be improved, which the users can do by calibrating the virtual tissues’ resistance. The evaluation of visual aspects was influenced by the participants’ experience, according to ANOVA test (F=15.6, p=0.0002, with p<0.01). The user preferences were the simulator with two viewpoints, objects with texture based on images and the device with a syringe coupled to it.Conclusion The simulation was considered thoroughly satisfactory for the anesthesia training, considering the needle insertion task, which includes the correct insertion point and depth, as well as the perception of tissues resistances during the insertion.

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Software testing activities account for a considerable portion of systems development cost and, for this reason, many studies have sought to automate these activities. Test data generation has a high cost reduction potential (especially for complex domain systems), since it can decrease human effort. Although several studies have been published about this subject, articles of reviews covering this topic usually focus only on specific domains. This article presents a systematic mapping aiming at providing a broad, albeit critical, overview of the literature in the topic of test data generation using genetic algorithms. The selected studies were categorized by software testing technique (structural, functional, or mutation testing) for which test data were generated and according to the most significantly adapted genetic algorithms aspects. The most used evaluation metrics and software testing techniques were identified. The results showed that genetic algorithms have been successfully applied to simple test data generation, but are rarely used to generate complex test data such as images, videos, sounds, and 3D (three-dimensional) models. From these results, we discuss some challenges and opportunities for research in this area.

This paper presents part of the implementation of a Virtual Reality (VR) framework, involving the building of an interaction module with support to conventional and non-conventional devices, and the evaluation of a system prototype, considering computational and human aspects. The proposal of the evaluation is to improve the framework, and consequently, the applications generated by it, following ideas and opinions of health's professionals (doctors and students), who are the target public of this project.

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