ArticleFrontiers in neuroscience2021
Adaptive Filtering for Improved EEG-Based Mental Workload Assessment of Ambulant Users.
Article in Frontiers in neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 37 citations in OpenAlex.
- Non-Invasive Physiological Metrics for Cognitive Load Assessment in Training and Operational Contexts: Signal Processing, Evidence, and Feasibility.Sensors (Basel, Switzerland) · 2026Review
- Assessment of cognitive load through photoplethysmography and bioimpedance responses during mental arithmetic tasks.Scientific reports · 2026Article
- Self-Supervised Learning with Adaptive Frequency-Time Attention Transformer for Seizure Prediction and Classification.Brain sciences · 2025Article
- Measuring Bound Attention During Complex Liver Surgery Planning: Feasibility Study.JMIR formative research · 2025Article
- Evaluating the efficiency and ergonomics of a novel smart surgical lighting system: a passive oddball experiment with EEG measurements to assess workplace strain in clinical settings.Frontiers in medical technology · 2025Article
- An Empirical Model-Based Algorithm for Removing Motion-Caused Artifacts in Motor Imagery EEG Data for Classification Using an Optimized CNN Model.Sensors (Basel, Switzerland) · 2024Article
- Blink-Related Oscillations Provide Naturalistic Assessments of Brain Function and Cognitive Workload within Complex Real-World Multitasking Environments.Sensors (Basel, Switzerland) · 2024Article
- MATB for assessing different mental workload levels.Frontiers in physiology · 2024Review
- Removal of movement artifacts and assessment of mental stress analyzing electroencephalogram of non-driving passengers under whole-body vibration.Frontiers in neuroscience · 2024Article
- Evidence for modulation of EEG microstates by mental workload levels and task types.Human brain mapping · 2024Article
- Quantifying time perception during virtual reality gameplay using a multimodal biosensor-instrumented headset: a feasibility study.Frontiers in neuroergonomics · 2023Article
- Methods for motion artifact reduction in online brain-computer interface experiments: a systematic review.Frontiers in human neuroscience · 2023Review
- A simplified design of a cEEGrid ear-electrode adapter for the OpenBCI biosensing platform.HardwareX · 2022Article
- Modulation Spectral Signal Representation for Quality Measurement and Enhancement of Wearable Device Data: A Technical Note.Sensors (Basel, Switzerland) · 2022Review
- Immersive media experience: a survey of existing methods and tools for human influential factors assessment.Quality and user experience · 2022Review
- EEG-TNet: An End-To-End Brain Computer Interface Framework for Mental Workload Estimation.Frontiers in neuroscience · 2022Article
- Affective Neurofeedback Under Naturalistic Conditions: A Mini-Review of Current Achievements and Open Challenges.Frontiers in neuroergonomics · 2021Review
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recently, due to the emergence of mobile electroencephalography (EEG) devices, assessment of mental workload in highly ecological settings has gained popularity. In such settings, however, motion and other common artifacts have been shown to severely hamper signal quality and to degrade mental workload assessment performance. Here, we show that classical EEG enhancement algorithms, conventionally developed to remove ocular and muscle artifacts, are not optimal in settings where participant movement (e.g., walking or running) is expected. As such, an adaptive filter is proposed that relies on an accelerometer-based referential signal. We show that when combined with classical algorithms, accurate mental workload assessment is achieved. To test the proposed algorithm, data from 48 participants was collected as they performed the Revised Multi-Attribute Task Battery-II (MATB-II) under a low and a high workload setting, either while walking/jogging on a treadmill, or using a stationary exercise bicycle. Accuracy as high as 95% could be achieved with a random forest based mental workload classifier with ambulant users. Moreover, an increase in gamma activity was found in the parietal cortex, suggesting a connection between sensorimotor integration, attention, and workload in ambulant users.
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Registered trials
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.