Enhancing mental workload recognition: a comparison of complexity-based eye movement metrics and conventional features
3.60T1 sourceErgonomics (Taylor & Francis)
Source record
Published by Ergonomics (Taylor & Francis) (T1 source). The original is at https://www.tandfonline.com/doi/full/10.1080/00140139.2025.2575068?af=R.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryPeer-reviewed study comparing complexity-based eye movement metrics against conventional features for recognizing mental workload, evaluating their relative performance in classification tasks.
Why it mattersEmpirical head-to-head of feature families for workload detection, useful for researchers selecting eye-tracking inputs for HCI or adaptive systems.
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