ArticleSensors (Basel, Switzerland)2023
Reliability of Mental Workload Index Assessed by EEG with Different Electrode Configurations and Signal Pre-Processing Pipelines.
Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Multimodal Evaluation of Mental Workload and Engagement in Upper-Limb Robot-Assisted Motor Tasks.Sensors (Basel, Switzerland) · 2026Article
- Cognitive load gating system in motor imagery BCIs: a dual-task EEG study with differential entropy-based reliability estimation.Frontiers in artificial intelligence · 2026Article
- From motor primitives to context-dependent coordination: a system neuroscience approach integrating cognitive, affective, and experiential factors into muscle synergy analysis.Frontiers in systems neuroscience · 2026Article
- Mapping EEG Metrics to Human Affective and Cognitive Models: An Interdisciplinary Scoping Review from a Cognitive Neuroscience Perspective.Biomimetics (Basel, Switzerland) · 2025Review
- Evaluating the performance of the cognitive workload model with subjective endorsement in addition to EEG.Medical & biological engineering & computing · 2024Article
- Reproducible machine learning research in mental workload classification using EEG.Frontiers in neuroergonomics · 2024Review
- Biomedical Sensors for Functional Mapping: Techniques, Methods, Experimental and Medical Applications.Sensors (Basel, Switzerland) · 2023Article
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5 authors.
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Abstract
BACKGROUND AND
objectiveMental workload (MWL) is a relevant construct involved in all cognitively demanding activities, and its assessment is an important goal in many research fields. This paper aims at evaluating the reproducibility and sensitivity of MWL assessment from EEG signals considering the effects of different electrode configurations and pre-processing pipelines (PPPs).
methodsThirteen young healthy adults were enrolled and were asked to perform 45 min of Simon's task to elicit a cognitive demand. EEG data were collected using a 32-channel system with different electrode configurations (fronto-parietal; Fz and Pz; Cz) and analyzed using different PPPs, from the simplest bandpass filtering to the combination of filtering, Artifact Subspace Reconstruction (ASR) and Independent Component Analysis (ICA). The reproducibility of MWL indexes estimation and the sensitivity of their changes were assessed using Intraclass Correlation Coefficient and statistical analysis.
resultsMWL assessed with different PPPs showed reliability ranging from good to very good in most of the electrode configurations (average consistency > 0.87 and average absolute agreement > 0.92). Larger fronto-parietal electrode configurations, albeit being more affected by the choice of PPPs, provide better sensitivity in the detection of MWL changes if compared to a single-electrode configuration (18 vs. 10 statistically significant differences detected, respectively).
conclusionsThe most complex PPPs have been proven to ensure good reliability (>0.90) and sensitivity in all experimental conditions. In conclusion, we propose to use at least a two-electrode configuration (Fz and Pz) and complex PPPs including at least the ICA algorithm (even better including ASR) to mitigate artifacts and obtain reliable and sensitive MWL assessment during cognitive tasks.
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