Video Game Playtesting with Physiological Data Acquisition
During video game playtests, feedback is collected via manual observations by playtest managers and retrospective evaluations from the playtesters. While this information is invaluable for game designers to optimize gameplay experiences, humans often cannot observe internal states and subtle emotional and physiological responses in real-time. This project validated the viability of using facial electromyography (fEMG) and subsequent data analysis methods to flag notable events during gameplay. The team delivered a system consisting of a well-documented experimental setup, an algorithm for feature extraction and statistical analysis, and a comprehensive report of findings with fEMG and other sensors investigated. This system will augment, rather than replace, the current playtesting system employed by Valve.
Faculty Advisor
Lynn Andrea Stein
Team Members
Bryan Werth
Vivien Chen
Minju Kang
Blake Blancett
Project Poster
Summit Breakout Session
