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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


 SCOPE Valve