{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T16:52:31Z","timestamp":1792687951747,"version":"4.5.0"},"reference-count":70,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100008045","name":"Nanjing University of Information Science and Technology","doi-asserted-by":"publisher","award":["2020r075"],"award-info":[{"award-number":["2020r075"]}],"id":[{"id":"10.13039\/501100008045","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62206130"],"award-info":[{"award-number":["62206130"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004608","name":"Jiangsu Province Natural Science Foundation","doi-asserted-by":"publisher","award":["BK20200821"],"award-info":[{"award-number":["BK20200821"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.fr","clinicalkey.jp","clinicalkey.es","clinicalkey.com.au","clinicalkey.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computer Methods and Programs in Biomedicine"],"published-print":{"date-parts":[[2025,6]]},"DOI":"10.1016\/j.cmpb.2025.108714","type":"journal-article","created":{"date-parts":[[2025,3,7]],"date-time":"2025-03-07T16:12:49Z","timestamp":1741363969000},"page":"108714","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":14,"special_numbering":"C","title":["A comprehensive exploration of motion sickness process analysis from EEG signal and virtual reality"],"prefix":"10.1016","volume":"264","author":[{"given":"Naishi","family":"Feng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9713-7737","authenticated-orcid":false,"given":"Bin","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-7033-9762","authenticated-orcid":false,"given":"Qianqian","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chengcheng","family":"Hua","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5093-2672","authenticated-orcid":false,"given":"Yue","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.cmpb.2025.108714_bib0001","doi-asserted-by":"crossref","first-page":"18043","DOI":"10.1038\/s41598-022-21307-z","article-title":"EEG-based analysis of various sensory stimulation effects to reduce visually induced motion sickness in virtual reality","volume":"12","author":"Yeo","year":"2022","journal-title":"Sci. Rep."},{"key":"10.1016\/j.cmpb.2025.108714_bib0002","doi-asserted-by":"crossref","first-page":"2073","DOI":"10.1007\/s10055-023-00795-y","article-title":"Brain activity during cybersickness: a scoping review","volume":"27","author":"Chang","year":"2023","journal-title":"Virt. Real."},{"key":"10.1016\/j.cmpb.2025.108714_bib0003","doi-asserted-by":"crossref","first-page":"1658","DOI":"10.1080\/10447318.2020.1778351","article-title":"Virtual reality sickness: A review of causes and measurements","volume":"36","author":"Chang","year":"2020","journal-title":"Int. J. Hum.-Comput. Interact."},{"key":"10.1016\/j.cmpb.2025.108714_bib0004","doi-asserted-by":"crossref","DOI":"10.1016\/j.displa.2023.102415","article-title":"Effects of speed, complexity and stereoscopic VR cues on cybersickness examined via EEG and self-reported measures","volume":"78","author":"Ozkan","year":"2023","journal-title":"Displays"},{"key":"10.1016\/j.cmpb.2025.108714_bib0005","doi-asserted-by":"crossref","first-page":"108944","DOI":"10.1109\/ACCESS.2023.3320043","article-title":"VR Vertigo level classification using a multi-dimensional Taylor Network approach","volume":"11","author":"Wang","year":"2023","journal-title":"IEEE Access"},{"key":"10.1016\/j.cmpb.2025.108714_bib0006","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1207\/s15326969eco0303_2","article-title":"An ecological theory of motion sickness and postural instability","volume":"3","author":"Riccio","year":"1991","journal-title":"Ecol. Psychol."},{"key":"10.1016\/j.cmpb.2025.108714_bib0007","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1207\/s15327108ijap0303_3","article-title":"Simulator sickness questionnaire: an enhanced method for quantifying Simulator sickness","volume":"3","author":"Kennedy","year":"1993","journal-title":"Int. J. Aviat. Psychol."},{"key":"10.1016\/j.cmpb.2025.108714_bib0008","doi-asserted-by":"crossref","first-page":"2463","DOI":"10.1007\/s00221-023-06690-x","article-title":"Exploring neurophysiological correlates of visually induced motion sickness using electroencephalography (EEG)","volume":"241","author":"Andrievskaia","year":"2023","journal-title":"Exp. Brain Res."},{"key":"10.1016\/j.cmpb.2025.108714_bib0009","first-page":"945","article-title":"Individual differences in neural processing of rest frames during virtual reality navigation","volume":"16","author":"Chang","year":"2021","journal-title":"Knowl. Inf. Syst."},{"key":"10.1016\/j.cmpb.2025.108714_bib0010","doi-asserted-by":"crossref","first-page":"2862","DOI":"10.1016\/j.neuroimage.2009.10.005","article-title":"Spatial and temporal EEG dynamics of motion sickness","volume":"49","author":"Chen","year":"2010","journal-title":"Neuroimage"},{"key":"10.1016\/j.cmpb.2025.108714_bib0011","doi-asserted-by":"crossref","DOI":"10.1016\/j.apergo.2022.103731","article-title":"Estimating objective (EEG) and subjective (SSQ) cybersickness in people with susceptibility to motion sickness","volume":"102","author":"Jang","year":"2022","journal-title":"Appl. Ergon."},{"key":"10.1016\/j.cmpb.2025.108714_bib0012","doi-asserted-by":"crossref","DOI":"10.1016\/j.neulet.2020.135589","article-title":"Test-retest reliability of the virtual reality sickness evaluation using electroencephalography (EEG)","volume":"743","author":"Lim","year":"2021","journal-title":"Neurosci. Lett."},{"key":"10.1016\/j.cmpb.2025.108714_bib0013","doi-asserted-by":"crossref","first-page":"721","DOI":"10.1007\/s13246-015-0379-9","article-title":"EEG based time and frequency dynamics analysis of visually induced motion sickness (VIMS)","volume":"38","author":"Naqvi","year":"2015","journal-title":"Australas. Phys. Eng. Sci. Med."},{"key":"10.1016\/j.cmpb.2025.108714_bib0014","doi-asserted-by":"crossref","first-page":"535","DOI":"10.17337\/JMBI.2019.21.4.535","article-title":"A study on visual fatigue and binocular visual function before and after watching VR image","volume":"21","author":"Son","year":"2019","journal-title":"Korean J. Vision Sci."},{"key":"10.1016\/j.cmpb.2025.108714_bib0015","first-page":"1","article-title":"Effects of system-and media-driven immersive capabilities on presence and affective experience","volume":"27","author":"Standen","year":"2023","journal-title":"Virt. Real."},{"key":"10.1016\/j.cmpb.2025.108714_bib0016","doi-asserted-by":"crossref","DOI":"10.1155\/2015\/523250","article-title":"Effects of exercise in immersive virtual environments on cortical neural oscillations and mental state","volume":"2015","author":"Vogt","year":"2015","journal-title":"Neural Plast."},{"key":"10.1016\/j.cmpb.2025.108714_bib0017","doi-asserted-by":"crossref","DOI":"10.1016\/j.heliyon.2023.e14792","article-title":"Recovery time from VR sickness due to susceptibility: objective and quantitative evaluation using electroencephalography","volume":"9","author":"Woo","year":"2023","journal-title":"Heliyon"},{"key":"10.1016\/j.cmpb.2025.108714_bib0018","doi-asserted-by":"crossref","DOI":"10.3389\/fnhum.2021.757735","article-title":"Mismatch of visual-vestibular information in virtual reality: is motion sickness part of the brains attempt to reduce the prediction error?","volume":"15","author":"N\u00fcrnberger","year":"2021","journal-title":"Front. Hum. Neurosci."},{"key":"10.1016\/j.cmpb.2025.108714_bib0019","doi-asserted-by":"crossref","DOI":"10.1155\/2020\/5758038","article-title":"Too real to Be virtual: autonomic and EEG responses to extreme stress scenarios in virtual reality","volume":"2020","author":"Fadeev","year":"2020","journal-title":"Behav. Neurol."},{"key":"10.1016\/j.cmpb.2025.108714_bib0020","doi-asserted-by":"crossref","first-page":"1323","DOI":"10.1007\/s42835-020-00373-1","article-title":"EEG studies on physical discomforts induced by virtual reality gaming","volume":"15","author":"Heo","year":"2020","journal-title":"J. Electr. Eng. Technol."},{"key":"10.1016\/j.cmpb.2025.108714_bib0021","doi-asserted-by":"crossref","DOI":"10.1002\/cav.1953","article-title":"Exploring neural and peripheral physiological correlates of simulator sickness","volume":"31","author":"Tauscher","year":"2020","journal-title":"Comput. Anim. Virtual Worlds"},{"key":"10.1016\/j.cmpb.2025.108714_bib0022","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1007\/s10055-021-00517-2","article-title":"Quantifying VR cybersickness using EEG","volume":"26","author":"Krokos","year":"2022","journal-title":"Virt. Real."},{"key":"10.1016\/j.cmpb.2025.108714_bib0023","doi-asserted-by":"crossref","DOI":"10.1016\/j.cmpb.2019.105266","article-title":"VR motion sickness recognition by using EEG rhythm energy ratio based on wavelet packet transform","volume":"188","author":"Li","year":"2020","journal-title":"Comput. Methods Programs Biomed."},{"key":"10.1016\/j.cmpb.2025.108714_bib0024","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2352\/J.ImagingSci.Technol.2020.64.2.020501","article-title":"A pilot study on electroencephalogram-based evaluation of visually induced motion sickness","volume":"64","author":"Liu","year":"2020","journal-title":"J. Imaging Sci. Technol."},{"key":"10.1016\/j.cmpb.2025.108714_bib0025","first-page":"1651","article-title":"Parsimonious approach to in analyzing brainwaves for VR users","volume":"21","author":"Oh","year":"2022","journal-title":"J. Web Eng."},{"key":"10.1016\/j.cmpb.2025.108714_bib0026","doi-asserted-by":"crossref","first-page":"2379","DOI":"10.1109\/TVCG.2024.3372066","article-title":"Who says you are so sick? An investigation on individual susceptibility to cybersickness triggers using EEG, EGG and ECG","volume":"30","author":"Tian","year":"2024","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"10.1016\/j.cmpb.2025.108714_bib0027","doi-asserted-by":"crossref","DOI":"10.1016\/j.physbeh.2024.114626","article-title":"Detection of virtual reality motion sickness based on EEG using asymmetry of entropy and cross-frequency coupling","volume":"284","author":"Hua","year":"2024","journal-title":"Physiol. Behav."},{"key":"10.1016\/j.cmpb.2025.108714_bib0028","doi-asserted-by":"crossref","first-page":"2469","DOI":"10.1109\/JBHI.2021.3134024","article-title":"Multimodal biosensing for vestibular network-based cybersickness detection","volume":"26","author":"Li","year":"2021","journal-title":"IEEE J. Biomed. Health. Inf."},{"key":"10.1016\/j.cmpb.2025.108714_bib0029","doi-asserted-by":"crossref","unstructured":"M. Dennison, M. D'Zmura, A. Harrison, M. Lee, A. Raglin, Improving motion sickness severity classification through multi-modal data fusion, 11006 (2019), 10.1117\/12.2519085.","DOI":"10.1117\/12.2519085"},{"key":"10.1016\/j.cmpb.2025.108714_bib0030","doi-asserted-by":"crossref","DOI":"10.3389\/frvir.2022.973236","article-title":"Prediction of cybersickness in virtual environments using topological data analysis and machine learning","volume":"3","author":"Hadadi","year":"2022","journal-title":"Front. Virtual Real."},{"key":"10.1016\/j.cmpb.2025.108714_bib0031","doi-asserted-by":"crossref","first-page":"3936","DOI":"10.3390\/s24123936","article-title":"Classification of visually induced motion sickness based on phase-locked value functional connectivity matrix and CNN-LSTM","volume":"24","author":"Shen","year":"2024","journal-title":"Sensors"},{"key":"10.1016\/j.cmpb.2025.108714_bib0032","doi-asserted-by":"crossref","DOI":"10.3389\/fnins.2020.600839","article-title":"Temporal dynamics of visually induced motion perception and neural evidence of alterations in the motion perception process in an immersive virtual reality environment","volume":"14","author":"Ahn","year":"2020","journal-title":"Front. Neurosci."},{"key":"10.1016\/j.cmpb.2025.108714_bib0033","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1186\/s40708-023-00192-w","article-title":"Prediction and detection of virtual reality induced cybersickness: a spiking neural network approach using spatiotemporal EEG brain data and heart rate variability","volume":"10","author":"Yang","year":"2023","journal-title":"Brain Inf"},{"key":"10.1016\/j.cmpb.2025.108714_bib0034","doi-asserted-by":"crossref","first-page":"24839","DOI":"10.1109\/JSEN.2023.3309260","article-title":"Assessment of virtual reality motion sickness severity based on EEG via LSTM\/BiLSTM","volume":"23","author":"Hua","year":"2023","journal-title":"IEEE Sens. J."},{"key":"10.1016\/j.cmpb.2025.108714_bib0035","doi-asserted-by":"crossref","first-page":"2895","DOI":"10.1109\/TCSVT.2021.3103544","article-title":"Assessing individual VR sickness through deep feature fusion of VR video and physiological response","volume":"32","author":"Lee","year":"2022","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.cmpb.2025.108714_bib0036","doi-asserted-by":"crossref","first-page":"126784","DOI":"10.1109\/ACCESS.2020.3008165","article-title":"Using EEG and Deep learning to predict motion sickness under wearing a virtual reality device","volume":"8","author":"Liao","year":"2020","journal-title":"IEEE Access"},{"key":"10.1016\/j.cmpb.2025.108714_bib0037","article-title":"Exploring quantitative assessment of cybersickness in virtual reality using EEG signals and a CNN-ECA-LSTM network","volume":"81","author":"Liu","year":"2023","journal-title":"Displays"},{"key":"10.1016\/j.cmpb.2025.108714_bib0038","article-title":"VIMSNet: an effective network for visually induced motion sickness detection","volume":"16","author":"Liu","year":"2022","journal-title":"Sig. Image Video Process."},{"key":"10.1016\/j.cmpb.2025.108714_bib0039","doi-asserted-by":"crossref","DOI":"10.1016\/j.displa.2024.102704","article-title":"CDMS: a real-time system for EEG-guided cybersickness mitigation through adaptive adjustment of VR content factors","volume":"83","author":"Uyan","year":"2024","journal-title":"Displays"},{"key":"10.1016\/j.cmpb.2025.108714_bib0040","doi-asserted-by":"crossref","unstructured":"Z. Wang, Y. Yan, J. Cai, C. Hua, N. Liu, Q. Chen, M. Li, D. Zhang, - VR Vertigo level classification using a multi-dimensional Taylor Network approach, - 11 (2023) - 108955.","DOI":"10.1109\/ACCESS.2023.3320043"},{"key":"10.1016\/j.cmpb.2025.108714_bib0041","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/j.neuroimage.2019.05.026","article-title":"ICLabel: an automated electroencephalographic independent component classifier, dataset, and website","volume":"198","author":"Pion-Tonachini","year":"2019","journal-title":"Neuroimage"},{"key":"10.1016\/j.cmpb.2025.108714_bib0042","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2019.101702","article-title":"A review of feature extraction and performance evaluation in epileptic seizure detection using EEG","volume":"57","author":"Boonyakitanont","year":"2020","journal-title":"Biomed. Signal Process. Control."},{"key":"10.1016\/j.cmpb.2025.108714_bib0043","doi-asserted-by":"crossref","first-page":"1525","DOI":"10.3390\/brainsci11111525","article-title":"Neural decoding of EEG signals with machine learning: a systematic review","author":"Saeidi","year":"2021","journal-title":"Brain Sci."},{"key":"10.1016\/j.cmpb.2025.108714_bib0044","doi-asserted-by":"crossref","DOI":"10.3389\/frai.2022.1072801","article-title":"Trends in EEG signal feature extraction applications","volume":"5","author":"Singh","year":"2023","journal-title":"Front. Artif. Intell."},{"key":"10.1016\/j.cmpb.2025.108714_bib0045","doi-asserted-by":"crossref","first-page":"3616","DOI":"10.3390\/app10103616","article-title":"Time-series prediction of the oscillatory phase of EEG signals using the least mean square algorithm-based AR model","author":"Shakeel","year":"2020","journal-title":"Appl. Sci."},{"key":"10.1016\/j.cmpb.2025.108714_bib0046","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0199144","article-title":"Dynamical Hurst analysis identifies EEG channel differences between PTSD and healthy controls","volume":"13","author":"Rahmani","year":"2018","journal-title":"PLoS One"},{"key":"10.1016\/j.cmpb.2025.108714_bib0047","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1007\/s10470-019-01388-z","article-title":"Application of fractal dimension for EEG based diagnosis of encephalopathy","volume":"100","author":"Jacob","year":"2019","journal-title":"Analog. Integr. Circuits. Signal. Process."},{"key":"10.1016\/j.cmpb.2025.108714_bib0048","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.cmpb.2016.05.014","article-title":"Application of Higuchi's fractal dimension from basic to clinical neurophysiology: a review","volume":"133","author":"Kesi\u0107","year":"2016","journal-title":"Comput. Methods Programs Biomed."},{"key":"10.1016\/j.cmpb.2025.108714_bib0049","series-title":"Proceedings of the 2005 European Conference on Circuit Theory and Design","first-page":"153","article-title":"Lyapunov exponent of EEG signal for epileptic seizure characterization","volume":"2005","author":"Swiderski","year":"2005"},{"key":"10.1016\/j.cmpb.2025.108714_bib0050","first-page":"209","article-title":"1D-local binary pattern based feature extraction for classification of epileptic EEG signals","volume":"243","author":"Kaya","year":"2014","journal-title":"Appl. Math. Comput."},{"key":"10.1016\/j.cmpb.2025.108714_bib0051","doi-asserted-by":"crossref","first-page":"150252","DOI":"10.1109\/ACCESS.2021.3126065","article-title":"Simple detection of epilepsy from EEG signal using local binary pattern transition histogram","volume":"9","author":"Yazid","year":"2021","journal-title":"IEEE Access"},{"key":"10.1016\/j.cmpb.2025.108714_bib0052","doi-asserted-by":"crossref","DOI":"10.3389\/fnhum.2021.746081","article-title":"Mental State detection using riemannian geometry on electroencephalogram brain signals","volume":"15","author":"Wriessnegger","year":"2021","journal-title":"Front. Hum. Neurosci."},{"key":"10.1016\/j.cmpb.2025.108714_bib0053","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1007\/s12021-020-09473-9","article-title":"Review of riemannian distances and divergences, applied to SSVEP-based BCI","volume":"19","author":"Chevallier","year":"2020","journal-title":"Neuroinformatics"},{"key":"10.1016\/j.cmpb.2025.108714_bib0054","article-title":"Deep learning for motor imagery EEG-based classification: a review","volume":"63","author":"Al-Saegh","year":"2021","journal-title":"Biomed. Sig. Process. Cont."},{"key":"10.1016\/j.cmpb.2025.108714_bib0055","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2023.107450","article-title":"Emotion recognition in EEG signals using deep learning methods: a review","volume":"165","author":"Jafari","year":"2023","journal-title":"Comput. Biol. Med."},{"key":"10.1016\/j.cmpb.2025.108714_bib0056","doi-asserted-by":"crossref","first-page":"842","DOI":"10.1038\/s41598-024-84429-6","article-title":"Cognitive load detection through EEG lead wise feature optimization and ensemble classification","volume":"15","author":"Yedukondalu","year":"2025","journal-title":"Sci. Rep."},{"key":"10.1016\/j.cmpb.2025.108714_bib0057","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.compedu.2016.12.003","article-title":"The effects of attention monitoring with EEG biofeedback on university students' attention and self-efficacy: the case of anti-phishing instructional materials","volume":"106","author":"Sun","year":"2017","journal-title":"Comput. Educ."},{"key":"10.1016\/j.cmpb.2025.108714_bib0058","first-page":"2007","article-title":"SVM-based gait control method for hydraulic quadruped robots","volume":"27","author":"Zhang","year":"2023","journal-title":"J. Appl. Sci. Eng."},{"key":"10.1016\/j.cmpb.2025.108714_bib0059","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1504\/IJBIC.2024.136729","article-title":"Design and verification of use case generation algorithm based on multiple combination tests","volume":"23","author":"Zheng","year":"2024","journal-title":"Int. J. Bio-Inspired Comput."},{"key":"10.1016\/j.cmpb.2025.108714_bib0060","article-title":"Jump motion intention recognition and brain activity analysis based on EEG signals and Vision Transformer model","volume":"100","author":"Lu","year":"2025","journal-title":"Biomed. Sig. Process. Cont."},{"key":"10.1016\/j.cmpb.2025.108714_bib0061","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.displa.2018.07.001","article-title":"Postural stability predicts the likelihood of cybersickness in active HMD-based virtual reality","volume":"58","author":"Arcioni","year":"2019","journal-title":"Displays"},{"key":"10.1016\/j.cmpb.2025.108714_bib0062","doi-asserted-by":"crossref","first-page":"771","DOI":"10.1080\/10447318.2017.1286767","article-title":"Features of the postural sway signal as indicators to estimate and predict visually induced motion sickness in virtual reality","volume":"33","author":"Chardonnet","year":"2017","journal-title":"Int. J. Human\u2013Comput. Interac."},{"key":"10.1016\/j.cmpb.2025.108714_bib0063","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1016\/j.humov.2019.03.006","article-title":"Unstable coupling of body sway with imposed motion precedes visually induced motion sickness","volume":"64","author":"Walter","year":"2019","journal-title":"Hum. Mov. Sci."},{"key":"10.1016\/j.cmpb.2025.108714_bib0064","doi-asserted-by":"crossref","first-page":"1830","DOI":"10.1177\/00187208211059623","article-title":"Using nonlinear kinematic parameters as a means of predicting motion sickness in real-time in virtual environments","volume":"65","author":"Smart","year":"2021","journal-title":"Hum. Factors."},{"key":"10.1016\/j.cmpb.2025.108714_bib0065","doi-asserted-by":"crossref","first-page":"2201","DOI":"10.1152\/jn.00477.2018","article-title":"Estimating the sensorimotor components of cybersickness","volume":"120","author":"Weech","year":"2018","journal-title":"J. Neurophysiol."},{"key":"10.1016\/j.cmpb.2025.108714_bib0066","doi-asserted-by":"crossref","first-page":"891","DOI":"10.1080\/00140139.2020.1869320","article-title":"User discomfort while using a virtual reality headset as a personal viewing system for text-intensive office tasks","volume":"64","author":"Kim","year":"2021","journal-title":"Ergonomics"},{"key":"10.1016\/j.cmpb.2025.108714_bib0067","series-title":"Proceedings of the 2023 3rd International Conference on Robotics and Control Engineering","first-page":"172","article-title":"The effect of additional shooting task on alleviating virtual reality motion sickness","author":"Hua","year":"2023"},{"key":"10.1016\/j.cmpb.2025.108714_bib0068","doi-asserted-by":"crossref","DOI":"10.1016\/j.entcom.2021.100423","article-title":"Variations in visual sensitivity predict motion sickness in virtual reality","volume":"38","author":"Fulvio","year":"2021","journal-title":"Entertain. Comput."},{"key":"10.1016\/j.cmpb.2025.108714_bib0069","article-title":"Virtual reality is sexist: but it does not have to Be","volume":"7","author":"Stanney","year":"2020","journal-title":"Front. Rob. AI."},{"key":"10.1016\/j.cmpb.2025.108714_bib0070","doi-asserted-by":"crossref","first-page":"1604","DOI":"10.3389\/fpsyg.2020.01604","article-title":"Are modern head-mounted displays sexist? A systematic review on gender differences in HMD-mediated virtual reality","volume":"11","author":"Grassini","year":"2020","journal-title":"Front. Psychol."}],"container-title":["Computer Methods and Programs in Biomedicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0169260725001312?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0169260725001312?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,4,8]],"date-time":"2025-04-08T23:39:39Z","timestamp":1744155579000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0169260725001312"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6]]},"references-count":70,"alternative-id":["S0169260725001312"],"URL":"https:\/\/doi.org\/10.1016\/j.cmpb.2025.108714","relation":{},"ISSN":["0169-2607"],"issn-type":[{"value":"0169-2607","type":"print"}],"subject":[],"published":{"date-parts":[[2025,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A comprehensive exploration of motion sickness process analysis from EEG signal and virtual reality","name":"articletitle","label":"Article Title"},{"value":"Computer Methods and Programs in Biomedicine","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cmpb.2025.108714","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"108714"}}