The field of game development and neurogaming is rapidly evolving, with a focus on enhancing player engagement, personalization, and immersion. Researchers are exploring innovative approaches to game development, including the use of experimentation, gamification, and brain-computer interfaces. The integration of artificial intelligence, machine learning, and neuroscientific techniques is enabling the creation of more sophisticated and adaptive gaming experiences. Notably, the use of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) is allowing for the development of neuroadaptive systems that can dynamically adjust game difficulty and feedback in real-time. Additionally, reinforcement learning is being applied to personalize therapeutic content and improve treatment outcomes. Overall, these advancements have the potential to revolutionize the gaming industry and beyond. Noteworthy papers include: The paper on Dynamic Difficulty Adjustment With Brain Waves presents a novel approach to optimizing player engagement using EEG-based brain wave monitoring. The paper on Personalizing Exposure Therapy via Reinforcement Learning demonstrates the effectiveness of using reinforcement learning to adapt therapeutic content to individual patients.
Advancements in Game Development and Neurogaming
Sources
Experimentation in Gaming: an Adoption Guide
Gamification as a Data Acquisition Strategy for Neurogames
Learning by gaming, coding and making with EDUMING: A new approach to utilising atypical digital games for learning
Hybrid Deep Learning Model to Estimate Cognitive Effort from fNIRS Signals in Educational Game Playing
Dynamic Difficulty Adjustment With Brain Waves as a Tool for Optimizing Engagement
Personalizing Exposure Therapy via Reinforcement Learning
Players' Perception of Bugs and Glitches in Video Games: An Exploratory Study
Neuroadaptive Haptics: Comparing Reinforcement Learning from Explicit Ratings and Neural Signals for Adaptive XR Systems