{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T06:17:30Z","timestamp":1788157050405,"version":"build-2803163510"},"reference-count":47,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2026,8,30]],"date-time":"2026-08-30T00:00:00Z","timestamp":1788048000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Science and Technology Major Project of Intelligent Manufacturing Systems and Robotics","award":["2025ZD1602803"],"award-info":[{"award-number":["2025ZD1602803"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Assessing visual fatigue is crucial in eye-controlled interaction. Traditional methods are either overly subjective or rely on highly invasive, costly equipment and complex procedures that require expert supervision. This study proposes a machine-learning-based approach for visual fatigue assessment. Data collection employs non-intrusive, easily monitored eye-tracking to capture ocular eye movement data and task performance data, while subjective questionnaires label fatigue states. For feature selection, participant-level Wilcoxon signed-rank tests with Benjamini\u2013Hochberg FDR correction were used to identify fatigue-related indicators, and a redundancy-removal step based on Spearman correlation yielded a final set of six non-redundant features. For the assessment method, we introduced a gradient boosting decision tree\u2013logistic regression (GBDT-LR) model whose hyperparameters are optimized via Bayesian optimization. All models were evaluated under a unified 5-fold stratified cross-validation framework with within-fold standardization and nested hyperparameter tuning. Results indicate that this model can effectively predict the state of visual fatigue. Compared with the performance of five other models\u2014gradient boosting decision tree (GBDT), logistic regression (LR), support vector machine (SVM), random forest (RF), and RF-SVM\u2014the proposed GBDT-LR model achieved an assessment accuracy of 89.79%, demonstrating strong predictive performance. This study provides an effective method for predicting visual fatigue in eye-controlled interaction, laying a research foundation for optimizing the user experience of eye-controlled interaction and promoting the sustainable development of eye-control technology.<\/jats:p>","DOI":"10.3390\/s26175507","type":"journal-article","created":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T05:55:56Z","timestamp":1788155756000},"page":"5507","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Assessment of Visual Fatigue Caused by Eye-Controlled Interaction Based on Task Performance and Pupillary Response with GBDT-LR"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3152-3643","authenticated-orcid":false,"given":"Hongwei","family":"Niu","sequence":"first","affiliation":[{"name":"Industrial and Systems Engineering Laboratory, School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China"},{"name":"Yangtze Delta Region Academy, Beijing Institute of Technology, Jiaxing 314019, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"funding-acquisition","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"}]},{"given":"Ziyi","family":"Zhao","sequence":"additional","affiliation":[{"name":"Industrial and Systems Engineering Laboratory, School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"}]},{"given":"Mingyu","family":"Ai","sequence":"additional","affiliation":[{"name":"Industrial and Systems Engineering Laboratory, School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China"},{"name":"Yangtze Delta Region Academy, Beijing Institute of Technology, Jiaxing 314019, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"data-curation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"conceptualization","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"}]},{"given":"Xiaonan","family":"Yang","sequence":"additional","affiliation":[{"name":"Industrial and Systems Engineering Laboratory, School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China"},{"name":"Yangtze Delta Region Academy, Beijing Institute of Technology, Jiaxing 314019, China"},{"name":"Key Laboratory of Industry Knowledge & Data Fusion Technology and Application, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"},{"role":"funding-acquisition","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"Xuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Design & Arts, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"project-administration","vocabulary":"credit"},{"role":"funding-acquisition","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"}]},{"given":"Haonan","family":"Fang","sequence":"additional","affiliation":[{"name":"Industrial and Systems Engineering Laboratory, School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"methodology","vocabulary":"credit"},{"role":"conceptualization","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Schuetz, I., Murdison, T.S., MacKenzie, K.J., and Zannoli, M. 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