TruVR: Trustworthy Cybersickness Detection using Explainable Machine Learning. (arXiv:2209.05257v1 [cs.HC])

Cybersickness can be characterized by nausea, vertigo, headache, eye strain,
and other discomforts when using virtual reality (VR) systems. The previously
reported machine learning (ML) and deep learning (DL) algorithms for detecting
(classification) and predicting (regression) VR cybersickness use black-box
models; thus, they lack explainability. Moreover, VR sensors generate a massive
amount of data, resulting in complex and large models. Therefore, having
inherent explainability in cybersickness detection models can significantly
improve the model's trustworthiness and provide insight into why and …

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