ArticleCognitive neurodynamics2019
Mental fatigue level detection based on event related and visual evoked potentials features fusion in virtual indoor environment.
Article in Cognitive neurodynamics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- Fatigue Monitoring Through Wearables: A State-of-the-Art Review.Frontiers in physiology · 2021Pooled it
- BCI-Based Rehabilitation on the Stroke in Sequela Stage.Neural plasticity · 2020Trial
- Improvement of BCI performance with bimodal SSMVEPs: enhancing response intensity and reducing fatigue.Frontiers in neuroscience · 2025Article
- Objective assessment of cognitive fatigue: a bibliometric analysis.Frontiers in neuroscience · 2024Review
- SSVEP unsupervised adaptive feature recognition method based on self-similarity of same-frequency signals.Frontiers in neuroscience · 2023Article
- A multi-modal brain-computer interface based on threshold discrimination and its application in wheelchair control.Cognitive neurodynamics · 2022Article
- Article
- Neural mechanism of visual information degradation from retina to V1 area.Cognitive neurodynamics · 2021Article
- A Muscular and Cerebral Physiological Indices Assessment for Stress Measuring during Virtual Wheelchair Guidance.Brain sciences · 2021Article
- Instantaneous mental workload assessment using time-frequency analysis and semi-supervised learning.Cognitive neurodynamics · 2020Article
- Brain-computer interface method based on light-flashing and motion hybrid coding.Cognitive neurodynamics · 2020Article
- Medium- and long-term functional behavior evaluations in an experimental focal ischemic stroke mouse model.Cognitive neurodynamics · 2020Article
- Adaptive Neuro-Fuzzy Fusion of Multi-Sensor Data for Monitoring a Pilot's Workload Condition.Sensors (Basel, Switzerland) · 2019Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The purpose of this work is to set up a model that can estimate the mental fatigue of users based on the fusion of relevant features extracted from Positive 300 (P300) and steady state visual evoked potentials (SSVEP) measured by electroencephalogram. To this end, an experimental protocol describes the induction of P300, SSVEP and mental workload (which leads to mental fatigue by varying time-on-task) in different scenarios where environmental artifacts are controlled (obstacles number, obstacles velocities, ambient luminosity). Ten subjects took part in the experiment (with two suffering from cerebral palsy). Their mission is to navigate along a corridor from a starting point A to a goal point B where specific flickering stimuli are introduced to perform the P300 task. On the other hand, SSVEP task is elicited thanks to 10 Hz flickering lights. Correlated features are considered as inputs to fusion block which estimates mental workload. In order to deal with uncertainties and heterogeneity of P300 and SSVEP features, Dempster-Shafer (D-S) evidential reasoning is introduced. As the goal is to assess the reliability for the estimation of mental fatigue levels, D-S is compared to multi layer perception and linear discriminant analysis. The results show that D-S globally outperforms the other classifiers (although its performance significantly decreases between healthy and palsied groups). Finally we discuss the feasibility of such a fusion proposal in real life situation.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.