Design and build a software or product for Microsoft Imagine Cup 2024 (C)
In the project “Mind Garden”, we explore the innovative integration of gaming and artificial intelligence (AI) in assessing mental health, particularly focusing on depression detection among teenagers. This final year project employs classic machine learning and deep learning models to analyse st...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/177289 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Summary: | In the project “Mind Garden”, we explore the innovative integration of gaming and artificial
intelligence (AI) in assessing mental health, particularly focusing on depression detection
among teenagers. This final year project employs classic machine learning and deep learning
models to analyse static and dynamic eye behaviours as indicators of depression states.
Utilizing ResNet18 with additional sequential layers alongside Random Forest with Synthetic
Minority Over-sampling Technique (SMOTE), we achieve significant accuracy in depression
detection, demonstrating the feasibility of non-invasive mental health evaluations.
Unlike conventional assessment tools and mental health interviews, "Mind Garden" invites
users into a game-based environment designed to provoke reflection and participation. Through
a series of carefully crafted mini-games embedded within a peaceful, visually appealing setting,
the project encourages players to dive into their own mental and emotional landscapes. This
approach not only engages users in a meaningful exploration of their mental health but also
gathers valuable behavioural data. The structured integration of these games with backend AI
algorithms facilitates a seamless blend of entertainment and psychological evaluation. |
---|