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

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.

Authors

Institutions

Publication Details

Journal
International Journal of Multidisciplinary Studies and Innovative Technologies
Published
2025-01-01
DOI
https://doi.org/10.36287/ijmsit.9.1.2
Primary Topic
Education and Learning Interventions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Emre Olca, Ceylin Alak
International Journal of Multidisciplinary Studies and Innovative Technologies
Education and Learning Interventions
article

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

Emre Olca, Ceylin Alak
article en

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.

International Journal of Multidisciplinary Studies and Innovative TechnologiesVol. 9(1)
Maltepe University (TR)
Openalex Percentile: Top 70%
Education and Learning Interventions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.