ArticleScientific data2025
Fatigue Characterization Multimodal Datasets for Stereo Vision in Mixed Reality.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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3 authors.
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Abstract
Head Mounted Displays (HMDs) employ mixed reality (MR) technologies across various fields, affording users immersive visual experiences. However, prolonged use of HMDs devices to watch stereoscopic content may lead to visual fatigue. This study explores stereo-visual fatigue induced by viewing MR visual stimuli, focusing on EEG and peripheral physiological signals. We recorded 24-channel EEG signals from 23 healthy participants and combined them with electrocardiogram (ECG), electrodermal activity (EDA), peripheral oxygen saturation (SpO2), respiratory, and skin temperature data from 13 participants. These physiological signal characteristics were extracted and combined into multimodal datasets. These datasets have shown significant effects in identifying visual fatigue through experimental verification. The study highlights the need for publicly available datasets to further investigate stereo-visual fatigue in an MR environment.
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