ArticleSensors (Basel, Switzerland)2023
iCanClean Improves Independent Component Analysis of Mobile Brain Imaging with EEG.
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 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 29 citations in OpenAlex.
- rTMS Modulates Static and Dynamic Brain Functional Networks in Children with Autism Spectrum Disorder: An EEG Microstate Study.Brain topography · 2026Trial
- Preprocessing on the Go: Practices in Gait-Related Mobile EEG.Psychophysiology · 2026Review
- Suppressing Non-Stationary Motion Artefacts in Mobile EEG Using Generalized Eigenvalue Decomposition.Sensors (Basel, Switzerland) · 2026Article
- Mobility Function and Aperiodic Electrocortical Activity in Younger and Older Adults.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2026Article
- Age differences in electrocortical dynamics during uneven terrain walking.bioRxiv : the preprint server for biology · 2025Article
- A Comparison of Approaches for Motion Artifact Removal from Wireless Mobile EEG During Overground Running.Sensors (Basel, Switzerland) · 2025Article
- Comparison of corticomuscular coherence under different balance paradigms in individuals with and without forward head posture.Scientific reports · 2025Article
- Gait speed-related changes in electrocortical activity in younger and older adults.Journal of neurophysiology · 2025Article
- Age differences in electrocortical dynamics during uneven terrain walking.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Unsupervised clustering of pre-ictal EEG in children: a reproducible and lightweight CPU-based workflow.Frontiers in neurology · 2025Article
- Neural Mass Modeling in the Cortical Motor Area and the Mechanism of Alpha Rhythm Changes.Sensors (Basel, Switzerland) · 2024Article
- Mobile neuroimaging: What we have learned about the neural control of human walking, with an emphasis on EEG-based research.Neuroscience and biobehavioral reviews · 2024Review
- Electrical brain activity during human walking with parametric variations in terrain unevenness and walking speed.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- A table tennis serve versus rally hit elicits differential hemispheric electrocortical power fluctuations.Journal of neurophysiology · 2023Article
- iCanClean Removes Motion, Muscle, Eye, and Line-Noise Artifacts from Phantom EEG.Sensors (Basel, Switzerland) · 2023Article
- Electrocortical activity correlated with locomotor adaptation during split-belt treadmill walking.The Journal of physiology · 2023Article
- Fourier Synchrosqueezing Transform-ICA-EMD Framework Based EOG-Biometric Sustainable and Continuous Authentication via Voluntary Eye Blinking Activities.Biomimetics (Basel, Switzerland) · 2023Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Motion artifacts hinder source-level analysis of mobile electroencephalography (EEG) data using independent component analysis (ICA). iCanClean is a novel cleaning algorithm that uses reference noise recordings to remove noisy EEG subspaces, but it has not been formally tested in a parameter sweep. The goal of this study was to test iCanClean’s ability to improve the ICA decomposition of EEG data corrupted by walking motion artifacts. Our primary objective was to determine optimal settings and performance in a parameter sweep (varying the window length and r2 cleaning aggressiveness). High-density EEG was recorded with 120 + 120 (dual-layer) EEG electrodes in young adults, high-functioning older adults, and low-functioning older adults. EEG data were decomposed by ICA after basic preprocessing and iCanClean. Components well-localized as dipoles (residual variance < 15%) and with high brain probability (ICLabel > 50%) were marked as ‘good’. We determined iCanClean’s optimal window length and cleaning aggressiveness to be 4-s and r2 = 0.65 for our data. At these settings, iCanClean improved the average number of good components from 8.4 to 13.2 (+57%). Good performance could be maintained with reduced sets of noise channels (12.7, 12.2, and 12.0 good components for 64, 32, and 16 noise channels, respectively). Overall, iCanClean shows promise as an effective method to clean mobile EEG data.
Indexed as
Identifiers
What OpenQuestion holds
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.