Design Process of a Self Adaptive Smart Serious Games Ecosystem
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866918154822746112 |
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| author | Tao, X. Chen, P. Tsami, M. Khayati, F. Eckert, M. |
| author_facet | Tao, X. Chen, P. Tsami, M. Khayati, F. Eckert, M. |
| contents | This paper outlines the design vision and planned evolution of Blexer v3, a modular and AI-driven rehabilitation ecosystem based on serious games. Building on insights from previous versions of the system, we propose a new architecture that aims to integrate multimodal sensing, real-time reasoning, and intelligent control. The envisioned system will include distinct modules for data collection, user state inference, and gameplay adaptation. Key features such as dynamic difficulty adjustment (DDA) and procedural content generation (PCG) are also considered to support personalized interventions. We present the complete conceptual framework of Blexer v3, which defines the modular structure and data flow of the system. This serves as the foundation for the next phase: the development of a functional prototype and its integration into clinical rehabilitation scenarios. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_04615 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Design Process of a Self Adaptive Smart Serious Games Ecosystem Tao, X. Chen, P. Tsami, M. Khayati, F. Eckert, M. Systems and Control Artificial Intelligence I.2.1 This paper outlines the design vision and planned evolution of Blexer v3, a modular and AI-driven rehabilitation ecosystem based on serious games. Building on insights from previous versions of the system, we propose a new architecture that aims to integrate multimodal sensing, real-time reasoning, and intelligent control. The envisioned system will include distinct modules for data collection, user state inference, and gameplay adaptation. Key features such as dynamic difficulty adjustment (DDA) and procedural content generation (PCG) are also considered to support personalized interventions. We present the complete conceptual framework of Blexer v3, which defines the modular structure and data flow of the system. This serves as the foundation for the next phase: the development of a functional prototype and its integration into clinical rehabilitation scenarios. |
| title | Design Process of a Self Adaptive Smart Serious Games Ecosystem |
| topic | Systems and Control Artificial Intelligence I.2.1 |
| url | https://arxiv.org/abs/2510.04615 |