Studies have shown that prolonged Human-Computer Interaction (HCI) fatigue can increase the risk of mental illness and lead to a higher probability of errors and accidents during operations. Virtual Reality (VR) technology can simultaneously stimulate multiple senses such as visual, auditory, and tactile, providing an immersive experience that enhances cognition and understanding. Therefore, this study collects multimodal data to develop evaluation methods for HCI fatigue and further explores the fatigue-relieving effects of VR technology by comparing it with flat video. Using a modular design, electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) data in the resting, fatigue-induced, and recovery states, eye movement data in the resting and fatigue-induced states, as well as subjective scale results after each state were collected from the participants. Preprocessing and statistical analysis are performed through data flow architecture. After fatigue induction, it was found that the degree of activation of brain areas, especially the Theta band of prefrontal cortex, occurred significantly higher, the effective connectivity in the Alpha and Theta bands occurred significantly lower, the subjects' pupil diameters decreased, the blink frequency increased, and subjective questionnaire scores increased, which verified the validity of the multimodal data for assessing HCI fatigue. Analyzing fatigue relief through subgroups, it was found that when using the natural grassland scene with soothing music, both flat video and VR had the ability to alleviate fatigue, which was manifested as a significant decrease in the Alpha band in the LPFC brain area and a decrease in the questionnaire score. Moreover, during the recovery state, it was found that compared to the video group, the VR group had significantly higher activation in the Alpha and Theta bands of the prefrontal cortex, while the video group had significantly higher effective connectivity than the VR group in the Alpha band. This study delved deeply into the multidimensional characterization of fatigue and investigated new scenarios for the use of VR, which can help to promote the use of VR and can be migrated to scenarios that require fatigue management and productivity enhancement.
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http://dx.doi.org/10.1109/TVCG.2025.3549581 | DOI Listing |
Studies have shown that prolonged Human-Computer Interaction (HCI) fatigue can increase the risk of mental illness and lead to a higher probability of errors and accidents during operations. Virtual Reality (VR) technology can simultaneously stimulate multiple senses such as visual, auditory, and tactile, providing an immersive experience that enhances cognition and understanding. Therefore, this study collects multimodal data to develop evaluation methods for HCI fatigue and further explores the fatigue-relieving effects of VR technology by comparing it with flat video.
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Department of Otolaryngology, Head and Neck Surgery, Tokai University School of Medicine, Shimokasuya, Isehara-city, Kanagawa, Japan.
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View Article and Find Full Text PDFJ Prosthet Dent
March 2025
Researcher, Department of Biomechanics, BTI Biotechnology Institute I + D, Miñano, Spain.
Statement Of Problem: The seal at the implant-abutment connection (IAC) is crucial for ensuring implant-prosthetic function and reducing the risk of peri-implant diseases. An accurate determination of the first IAC gap under realistic dynamic-loading conditions is needed to investigate current and future IAC designs.
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J Vis Exp
January 2025
Department of Bioengineering, Northeastern University;
Caenorhabditis elegans is a model organism widely used for studying biological processes. Its transparency and small size make it ideal for imaging tissues, cells, and subcellular structures. Traditional flat agar pads for imaging C.
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February 2025
Key Laboratory of Spectral Imaging Technology, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, China.
Traditional facial recognition is realized by facial recognition algorithms based on 2D or 3D digital images and has been well developed and has found wide applications in areas related to identification verification. In this work, we propose a novel live face detection (LFD) method by utilizing snapshot spectral imaging technology, which takes advantage of the distinctive reflected spectra from human faces. By employing a computational spectral reconstruction algorithm based on Tikhonov regularization, a rapid and precise spectral reconstruction with a fidelity of over 99% for the color checkers and various types of "face" samples has been achieved.
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