Modelling physiological sensor noise to movement-based virtual reality activities
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Data
2024-02-23
Título da revista
ISSN da revista
Título do Volume
Editora
Scitepress
Resumo
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.
Descrição
Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2024)
Palavras-chave
REALIDADE VIRTUAL, VIRTUAL REALITY, PROCESSAMENTO DE DADOS, DATA PROCESSING, BIOFEEDBACK, APRENDIZAGEM COMPUTACIONAL, MACHINE LEARNING
Citação
Lopes, P., Fachada, N., Fonseca, M., Gamboa, H. & Quaresma, C. (2024). Modelling Physiological Sensor Noise to Movement-Based Virtual Reality Activities. In Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSIGNALS 2024, vol. 1 (pp. 778-785), Rome, Italy. SciTePress/INSTICC. https://doi.org/10.5220/0012424200003657