Relax Your Neck

Introduction

Relax your neck is a single endless runner game that allows users to navigate the mustang and avoid obstacles to run as far as they can. Users can control the navigation of the mustang by moving their heads up and down to stretch their necks. However, unlike other endless running games, our game is kept at an average uniform speed to prevent any injury during our game. Users can open up the game and check if their daily goal is fulfilled. They have to achieve either the step goal or the game goal to ensure they have enough exercise.

For tracking users' faces, it uses Apple's AR Face Tracking Feature with the depth camera. For making the game, it uses Apple's SpriteKit and Sprite Scene. For recording users' scores, it uses the FSCalendar, SAConfetti, and UserDefaults.

Control

When you are at the homepage, just click "Play" for playing the game. If you want to check the record, just click the "My Page" button.

In the game, you will control the mustang by heading up/down.

If your face is not captured by the depth camera, the game may be paused.

WHERE TO DOWNLOAD

Note: This game requires an iPhone 7 or after since it requires a depth camera. Running this game also requires Xcode and an Apple Developer Account.

Github Link: https://github.com/XuanZhai/Relax_Your_Neck

1: Download the release file from Github.

2: Open "Relax Your Neck.xcworkspace."

3: Connect your XCode with your iPhone.

4: Set the developer account up and run the program.

5: Have fun!

Project MemberS

This is a project created by a group of 4 people.

1: Xuan Zhai - Game Programmer, Game Designer

2: Yongjia Xu - UI Designer, UI Programmer

3: John Zhang - Video and Resource Developer

4: ZiCheng Ge - Video and Resource Developer

About this Project

Although this is a project in the CS5323 Mobile Application class, we are trying to keep developing it and make it better.

Our next idea is to combine it with Machine Learning.

The difficulty of this game will be modified based on the users' previous scores. The machine learning model will learn users' past experiences and update the difficulty of the game every time before users play.