Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Working Memory01:24

Working Memory

1.3K
Working memory refers to a combination of components, including short-term memory and attention, that allow an individual to hold information temporarily as we perform cognitive tasks. It is an essential cognitive function that enables the execution of complex tasks such as problem-solving, comprehension, and reasoning. Unlike short-term memory, which simply involves the storage of information for a brief period, working memory involves the active manipulation and processing of this...
1.3K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Regulatory measures for mitigating physical and mental health impacts in aerospace environment: A systematic review.

Life sciences in space research·2025
Same author

Dataset of binocularly coded steady-state visual evoked potentials recorded with an augmented reality headset.

Scientific data·2025
Same author

Adaptive Neurofeedback Training Using a Virtual Reality Game Enhances Motor Imagery Performance in Brain-Computer Interfaces.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2025
Same author

Corrigendum to "Sendai virus-based immunoadjuvant in hydrogel vaccine intensity-modulated dendritic cells activation for suppressing tumorigenesis" [Bioact. Mater. 6 (2021) 3879-3891].

Bioactive materials·2025
Same author

Enhanced theta oscillations in the left temporoparietal region associated with refractory positive symptoms in schizophrenia.

Schizophrenia (Heidelberg, Germany)·2025
Same author

Cortical changes induced by increased cognitive task difficulty during dual task balancing correlate with postural instability in elders and patients with Parkinson's disease.

Journal of neural engineering·2025

Related Experiment Video

Updated: Apr 23, 2026

Estimate the Cognitive Load Using Electrocardiographic Measure: A Human-AI Collaborative Task
07:08

Estimate the Cognitive Load Using Electrocardiographic Measure: A Human-AI Collaborative Task

Published on: December 5, 2025

1.2K

An EEG-based mental workload estimator trained on working memory task can work well under simulated multi-attribute

Yufeng Ke1, Hongzhi Qi1, Feng He1

  • 1Laboratory of Neural Engineering and Rehabilitation, Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University Tianjin, China.

Frontiers in Human Neuroscience
|September 25, 2014
PubMed
Summary

This study demonstrates a new method to accurately estimate mental workload (MW) across different tasks using electroencephalogram (EEG) data. Feature selection improves EEG-based MW estimation for complex tasks, enhancing human-machine interaction.

Keywords:
EEGcross-taskfeature selectionmental workloadmulti-attribute taskpassive brain computer-interfaceworking memory task

More Related Videos

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks
06:57

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Published on: August 9, 2016

10.5K
Assessing Working Memory in Children: The Comprehensive Assessment Battery for Children – Working Memory (CABC-WM)
09:05

Assessing Working Memory in Children: The Comprehensive Assessment Battery for Children – Working Memory (CABC-WM)

Published on: June 12, 2017

31.1K

Related Experiment Videos

Last Updated: Apr 23, 2026

Estimate the Cognitive Load Using Electrocardiographic Measure: A Human-AI Collaborative Task
07:08

Estimate the Cognitive Load Using Electrocardiographic Measure: A Human-AI Collaborative Task

Published on: December 5, 2025

1.2K
Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks
06:57

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Published on: August 9, 2016

10.5K
Assessing Working Memory in Children: The Comprehensive Assessment Battery for Children – Working Memory (CABC-WM)
09:05

Assessing Working Memory in Children: The Comprehensive Assessment Battery for Children – Working Memory (CABC-WM)

Published on: June 12, 2017

31.1K

Area of Science:

  • Neuroscience
  • Human-Computer Interaction
  • Cognitive Engineering

Background:

  • Mental workload (MW) estimation using electroencephalogram (EEG) is crucial for adaptive human-machine interaction systems.
  • Current EEG-based MW classifiers often fail in cross-task scenarios due to task-specific patterns and workload variations.

Purpose of the Study:

  • To develop a robust EEG-based mental workload estimator that performs effectively across different tasks.
  • To address the challenge of task-specific EEG patterns in MW estimation.

Main Methods:

  • Employed cross-task performance-based feature selection (FS) combined with a regression model.
  • Trained the model on working memory tasks and tested its performance on a complex multi-attribute task (MAT).

Main Results:

  • Significantly improved MW estimation performance (COR: 0.740 ± 0.147 for FS data, 0.598 ± 0.161 for validation data) compared to using all features.
  • Demonstrated the existence of common MW-related EEG features across simple and complex tasks.

Conclusions:

  • Feature selection is a promising approach to enhance the generalizability of EEG-based MW estimators across tasks.
  • This method offers a viable strategy for measuring mental workload in diverse operational contexts, improving human-machine interaction.
  • Identified commonalities in EEG patterns related to mental workload between simple and complex tasks.