Modelling physiological sensor noise to movement-based virtual reality activities

This position paper proposes the hypothesis that physiological noise artefacts can be classified based on the type of movements performed by participants in Virtual Reality contexts. To assess this hypothesis, a detailed research plan is proposed to study the influence of movement on the quality of the captured physiological signals. This paper argues that the proposed plan can produce a valid model for classifying noisy physiological signal features, providing insights into the influence of movement on artefacts, while contributing to the development of movement-based filters and the implementation of best practices for using various associated technologies.