Fatigue Characterization Multimodal Datasets for Stereo Vision in Mixed Reality

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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Publication Details

Journal
Scientific Data
Published
2025-12-27
DOI
https://doi.org/10.1038/s41597-025-06474-8
Primary Topic
Virtual Reality Applications and Impacts
Type
article
Field-Weighted Citation Impact
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article

Fatigue Characterization Multimodal Datasets for Stereo Vision in Mixed Reality

Qi Li, Chunguang Tao, Yan Wu
Scientific Data
Virtual Reality Applications and Impacts
article

Fatigue Characterization Multimodal Datasets for Stereo Vision in Mixed Reality

Qi Li, Chunguang Tao, Yan Wu
article en

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.

Scientific DataVol. 13(1)
Changchun University of Science and Technology (CN), Zhongshan Hospital (CN), Jilin International Studies University (CN)
Openalex Percentile: Top 34%
Virtual Reality Applications and Impacts
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