RL-Based VR Games for Cognitive Therapy in Children and Young Adults with Movement Disorders

This repository features a series of VR games designed to enhance cognitive therapy and muscle movement for children and young adults with movement disorders by integrating Reinforcement Learning (RL) techniques.

Overview

This repository contains a collection of VR games designed to enhance cognitive therapy for children and young adults with movement disorders through the integration of Reinforcement Learning (RL) techniques. Movement disorders such as Dystonia, Chorea, Tremor, Myoclonus, Parkinsonism, Ataxia, Spasticity, and Tic disorders present significant challenges, particularly in terms of therapy engagement and progress tracking.

Overall Movement Disorder Stats

Architecture

Objectives

1. Enhance Engagement: Develop engaging and interactive VR games that improve adherence to cognitive therapy and reduce dropout rates caused by lack of motivation.
2. Objective Progress Tracking: Utilize RL to provide real-time, objective assessments of patient progress, addressing the limitations of conventional subjective evaluations.
3. Personalized Feedback: Implement RL-based mechanisms to deliver personalized feedback, optimizing therapy outcomes and ensuring that interventions are tailored to individual needs.

Key Features

1. Reinforcement Learning Integration: Employ RL algorithms to adapt game difficulty and provide personalized feedback based on user performance, enhancing motivation and therapeutic efficacy.
2. Innovative Game Mechanics: Design and develop VR games with engaging mechanics to maintain patient interest and make therapy sessions more enjoyable.
3. Progress Tracking Tools: Incorporate tools for real-time monitoring and objective tracking of patient progress, improving the ability to assess therapy effectiveness and make data-driven adjustments.

Project Demo Link