Affective computing has recently gained popularity, especially in the field of human-computer interaction systems, where effectively evoking and detecting emotions is of paramount importance to enhance users experience. However, several issues are hindering progress in the field. In fact, the complexity of emotions makes it difficult to understand their triggers and control their elicitation. Additionally, effective emotion recognition requires analyzing multiple sensor data, such as facial expressions and physiological signals. These factors combined make it hard to collect high-quality datasets that can be used for research purposes (e.g., development of emotion recognition algorithms). Despite these challenges, Virtual Reality (VR) holds promise as a solution. By providing a controlled and immersive environment, VR enables the replication of real-world emotional experiences and facilitates the tracking of signals indicative of emotional states. However, controlling emotion elicitation remains a challenging task also within VR. This research paper introduces the Magic Xroom, a VR platform designed to enhance control over emotion elicitation by leveraging the theory of flow. This theory establishes a mapping between an individuals skill levels, task difficulty, and perceived emotions. In the Magic Xroom, the users skill level is continuously assessed, and task difficulty is adjusted accordingly to evoke specific emotions. Furthermore, user signals are collected using sensors, and virtual panels are utilized to determine the ground truth emotional states, making the Magic Xroom an ideal platform for collecting extensive datasets. The paper provides detailed implementation information, highlights the main properties of the Magic Xroom, and presents examples of virtual scenarios to illustrate its abilities and capabilities.

翻译：情感计算近来日益受到关注，特别是在人机交互系统领域，有效诱发与检测情绪对于提升用户体验至关重要。然而，该领域的发展仍面临若干阻碍。事实上，情绪的复杂性使得理解其诱发因素并控制其激发过程变得困难。此外，有效的情绪识别需要分析多种传感器数据，例如面部表情与生理信号。这些因素共同导致难以收集可用于研究目的（如情绪识别算法开发）的高质量数据集。尽管存在这些挑战，虚拟现实技术展现出作为解决方案的潜力。通过提供受控的沉浸式环境，VR能够复现真实世界的情感体验，并促进对情绪状态指示信号的追踪。然而，即使在VR环境中，控制情绪诱发仍是一项艰巨任务。本研究论文介绍了神奇XRoom——一个基于心流理论设计、旨在增强情绪诱发控制力的VR平台。该理论建立了个人技能水平、任务难度与感知情绪之间的映射关系。在神奇XRoom中，系统持续评估用户技能水平，并据此调整任务难度以激发特定情绪。此外，平台通过传感器收集用户信号，并利用虚拟面板确定真实情绪状态，使其成为收集大规模数据集的理想平台。本文提供了详细的实现信息，重点阐述了神奇XRoom的主要特性，并通过虚拟场景示例展示了其功能与潜力。