Abstract: Systems presented herein may automatically and dynamically modify a video game being played by a user based at least in part on a determined or predicted emotional state of a user. Using one or more machine learning algorithms, a parameter function can be generated that uses sensory and/or biometric data obtained by monitoring a user playing a video game. Based on the sensory and/or biometric data, an emotional state of the user can be predicted. For example, it can be determined whether a user is likely to be bored, happy, or frightened while playing the video game. Based at least in part on the determination of the user's emotional state, the video game can be modified to improve positive feelings and reduce negative feelings occurring in response to the video game.

Abstract: Systems presented herein may automatically and dynamically modify a video game being played by a user based at least in part on a determined or predicted emotional state of a user. Using one or more machine learning algorithms, a parameter function can be generated that uses sensory and/or biometric data obtained by monitoring a user playing a video game. Based on the sensory and/or biometric data, an emotional state of the user can be predicted. For example, it can be determined whether a user is likely to be bored, happy, or frightened while playing the video game. Based at least in part on the determination of the user's emotional state, the video game can be modified to improve positive feelings and reduce negative feelings occurring in response to the video game.