# My proposal

My name is Makhabbat, and I am a sophomore at KAIST doing my Bachelor's degree in Industrial Design (ID: 20240935). The URL to the forked repository: [git.prototyping.id](https://git.prototyping.id/20240935/homework5).

<!-- I want to make atypical infinite runner game usually made for ADHD children. When I was in China, I had a chance to play ADHD-DTx game made for ADHD children and proven to improve their condition. You can't download or even find information about it outside the research paper, so I wanted to make one for myself, cause I drift a lot and would like to train my attention somehow. 
This is an extreme multitasking game, requiring you to do various things at once and fast.
The game has 5 lanes instead of typical 3, when game starts there will be text presented about which things you have to be collecting - various things will be falling along the game so you will have to hit only the ones you were instructed to at the beginning of the game,  also one in a while you will have to pass through 'gates' and you're supposed to pass through the one that is answer to the question given several seconds before, you also have to gather basic awards along the lanes and avoid basic obstacles.
In the original game that we played, there is an EEG headset that goes along the tablet that records the level of attentiveness to track, however I am thinking it can be just a something that gets reduced when you make too many mistakes. 
I want to make it using three.js, because my reason for taking this course is to eventually be able to use three.js. -->

# NeuroRunner: A Multitasking Cognitive Training Game 

NeuroRunner is an atypical, **cognitively demanding** _infinite runner_ inspired by digital therapeutics (DTx) designed for children with ADHD.
In Zhejiang University Summer Program, I had the chance to play a clinically tested ADHD-focused game that significantly improved sustained attention, but the **game isn’t publicly available** and information about it exists only inside [research papers](https://pubmed.ncbi.nlm.nih.gov/41490776/).

<img src="./IMG_9134.jpg" width="45%">
<img src="./IMG_9135.jpg" width="45%">

This project is my attempt to recreate that idea for myself — as someone who often drifts and wants a way to actively train attention through gameplay.
The result is an extreme multitasking runner built with three.js, designed to overload and strengthen attentional control, working memory, and task-switching.

# Core Concept

NeuroRunner is not a typical runner with 3 lanes — it uses 5 lanes, faster pacing, and continuous task switching.
Players must constantly track multiple rule sets at the same time, rewarding precision and penalizing mind-wandering.

The goal is to maintain cognitive engagement.

# Gameplay Description

1. Five-Lane Movement

    - move between 5 horizontal lanes instead of the standard 3.
    - forces higher spatial attention.

2. Instruction Phase

    At the start of each run:

    - The player is shown a **type of target item they must collect**.
    - Throughout the game, objects fall randomly on the screen.
    - Players must collect only the instructed items and avoid irrelevant ones using the **hit putton** on the right.

    This trains selective attention and working memory

3. Cognitive Gate Questions

    Every now and then:

    1. A question appears (simple math or logic).
    2. Several seconds later, gates along all 5 lanes appears ahead.
    3. The player must pass through the gate corresponding to the correct answer.

    This trains delayed **recall, task switching, and decision-making under pressure**

4. Rewards & Obstacles

    - Basic pickups that increase score
    - Standard obstacles that must be avoided

5. Attentiveness Meter

The original DTx game used an EEG headset to track attentiveness in real time.

For this project, I replace that hardware with a mistake-based attentiveness meter.
The meter decreases when:
    - You collect wrong items
    - You miss target items
    - You pass through the wrong gate
    - You hit obstacles
When the meter reaches zero → game over.

This approximates attentional lapse tracking without requiring EEG hardware.

# Library Used

I've been wanting to learn three.js since previous semester, so I want to try learning it, using this project.

# Challenges

Since this is a multitasking game, there will be a lot of things going on at once, I can't even imagien how I am gonna do that.