Fear Tracker

A hardware/software package to track how scared a person is

Source Code Link: https://github.com/andrade824/Fear-Tracker

Students at my school during their third year work in teams to build a project over the course of the school year (called a "Junior Project"). My team developed a hardware/software package that lets independent horror content creators (games, movies, etc.) track how scared a person is while experiencing their content. This involves an embedded system (placed on a user’s wrist) that grabs heart rate, sweat level, and motion data. This data is then wirelessly transmitted (via Bluetooth) over to a PC that has software (written using the Qt framework) to track the pieces of data in real time as well as to provide methods for analyzing the data afterwards.

This device is marketed towards horror game developers, horror movie makers, and livestreamers (people who stream videos of themselves playing games) of horror games. For content creators (game developers and movie makers) this device would provide a mechanism for quantizing just how scared their viewers are while they play/watch their game/movie. The data that was collected could then be reviewed in the context of gameplay at a later point in time to find out where their content exceeds in being scary and where it fails. This could also be used by livestreamers to show their audience just how scared they actually are while playing a horror game. This can help deepen the immersion an audience member has with the person streaming the video.

Wristboard (Embedded System)

• Sits on user’s wrist and grabs data from three sensors: heart-rate sensor, galvanic skin response sensor (sweat), and an accelerometer (for detecting jump-scares)
• Utilizes an 8-bit AVR microcontroller for data capture
• Uses a 32-bit ARM Cortex-M4 microcontroller for processing the data (calculating heart-rate, detecting jump-scares, and measuring sweat).
• Data is sent wirelessly to PC over a Bluetooth module

Stat-Tracking Software (Desktop PC)

• Displays all three sensor’s data in real-time
• Provides graphs for each piece of data that can be zoomed in and analyzed at a later time
• Written in C++ and utilizes the Qt framework for the GUI