用大模型生成个性化认知训练游戏，帮助认知障碍患者提升能力。
LETGAMES: An LLM-Powered Gamified Approach to Cognitive Training for Patients with Cognitive Impairment
- 基于大模型生成开放世界叙事游戏，针对不同认知领域设计挑战。
- 通过对话策略提供指导与陪伴，提升患者参与度与训练效果。
- 结合心理学评估体系，验证了个性化游戏在康复中的显著潜力。
将游戏作为认知障碍患者的治疗工具具有显著益处，但针对个体的高效游戏设计成本高昂。为此，我们提出一种基于大模型的自动化个性化治疗游戏设计方法LETGAMES。受《龙与地下城》启发，该方法生成开放世界交互式叙事游戏，不仅能定制针对特定认知领域的场景与挑战，还通过对话策略提供引导与陪伴。为验证其有效性，我们首创心理学基础评估协议LETGAMESEVAL，建立全面的康复评估指标体系。基于该体系，通过大模型评估器与人类专家评估的实验结果均表明，该方法具备显著潜力，可成为满足广泛需求的可及且个性化的认知训练解决方案。代码将在论文接收后开源。
原文摘要 · Abstract (English)
The application of games as a therapeutic tool for cognitive training is beneficial for patients with cognitive impairments. However, effective game design for individual patient is resource-intensive. To this end, we propose an LLM-powered method, \ours, for automated and personalized therapeutic game design. Inspired by the Dungeons & Dragons, LETGAMES generates an open-world interactive narrative game. It not only generates game scenarios and challenges that target specific cognitive domains, but also employs conversational strategies to offer guidance and companionship. To validate its efficacy, we pioneer a psychology-grounded evaluation protocol LETGAMESEVAL, establishing comprehensive metrics for rehabilitative assessment. Building upon this, our experimental results from both LLM-based assessors and human expert evaluations demonstrate the significant potential of our approach, positioning LETGAMES as a promising solution to the widespread need for more accessible and tailored cognitive training tools. Our code will be open-sourced upon acceptance.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。