Real-time affect detection in virtual reality: a technique based on a three-dimensional model of affect and EEG signals

Andres Pinilla; Jan-Niklas Voigt-Antons; Jaime Garcia; William Raffe; Sebastian Möller

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Real-time affect detection in virtual reality: a technique based on a three-dimensional model of affect and EEG signals

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Description: Exploring how to infer VR users' affective states from their EEG activity in real-time. We used supervised learning and conducted the experiment in Virtual Reality. Two feature selection methods are compared.

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The code used to analyse the data in this repository is available at https://github.com/aepinilla/affect_detection

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