Shinjin Kang1, Taiwoo Park2,*
Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 205-214, 2020, DOI:10.31209/2019.100000141
Abstract This paper describes an outlier detection system based on a multimodal
physiology data clustering algorithm in a PC gaming environment. The goal of
this system is to provide information on a game player’s abnormal behavior
with a bio-signal analysis. Using this information, the game platform can easily
identify players with abnormal behavior in specific events. To do this, we
propose a mouse device that measures the wearer's skin conductivity,
temperature, and motion. We also suggest a Dynamic Time Warping (DTW)
based clustering algorithm. The developed system examines the biometric
information of 50 players in a More >
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