A Smart Recommendation System for Early Diagnosis of Alzheimer’s Disease through Gamification in the Metaverse

Authors : Ceylin Alak, Emre Olca

Pages : 8-13

View : 80 | Download : 74

Publication Date : 2025-07-31

Article Type : Research Paper

Abstract :This project explores how gamification, virtual reality (VR), and artificial intelligence (AI) can work together to detect early signs of Alzheimer’s disease in a non-invasive way. By turning cognitive tests into an engaging VR game, users complete tasks that assess memory, problem-solving, and spatial reasoning, which are the key abilities affected by the disease. The game places users in a virtual environment where they perform tasks like identifying shapes, organizing objects, and solving basic math problems. Machine learning models, including Random Forests (RF) and Long Short-Term Memory (LSTM) networks, analyze the data from these tasks. While RF helps detect patterns in user responses, LSTM tracks changes over time, making the diagnosis more accurate. The game is planning to be designed using Unity for development, Blender for 3D objects, and Audacity for sound design. These tools will help create realistic and interactive experiences. Unlike traditional medical tests, this VR game makes the process more comfortable and less stressful for the users. By combining VR, AI, and gamification, this project introduces a new and effective way to detect Alzheimer’s early.
Keywords : Alzheimer’s Disease, Virtual Reality (VR), Gamification, Random Forests (RF), Long Short-Term Memory (LSTM)

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