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...

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Bibliographic Details
Main Author: Han, Zhize
Other Authors: Wesley Tan Chee Wah
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/177289
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Institution: Nanyang Technological University
Language: English
Description
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.