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

, Frontiers Production Office

doi:10.3389/frvir.2023.1267071

ERRATUM article

Front. Virtual Real. , 04 August 2023

Sec. Virtual Reality and Human Behaviour

Volume 4 - 2023 | https://doi.org/10.3389/frvir.2023.1267071

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

This article is an erratum on:

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

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

by Pinilla A, Voigt-Antons J-N, Garcia J, Raffe W and Möller S (2023). Front. Virtual Real. 3:964754. doi: 10.3389/frvir.2022.964754

Due to a production error, the Data Availability Statement was incorrect. The incorrect statement reads “The code used for analyzing the data is open source and available at https://github.com/aepinilla/affect detection.” The correct statement is “The code used for analyzing the data is open source and available at “https://github.com/aepinilla/affect_detection.”

The publisher apologizes for this mistake. The original version of this article has been updated.

Keywords: affect detection, electroencephalography, virtual reality, emotion, affective computing, supervised leaning, machine learning, feature selection

Citation: Frontiers Production Office (2023) Erratum: Real-time affect detection in virtual reality: a technique based on a three-dimensional model of affect and EEG signals. Front. Virtual Real. 4:1267071. doi: 10.3389/frvir.2023.1267071

Received: 25 July 2023; Accepted: 25 July 2023;
Published: 04 August 2023.

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Frontiers Editorial Office, Frontiers Media SA, Switzerland

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

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