ArticleEntropy (Basel, Switzerland)2022
Resting-State EEG in Alpha Rhythm May Be Indicative of the Performance of Motor Imagery-Based Brain-Computer Interface.
Article in Entropy (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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Who cites it
8 citing papers in PubMed, 21 citations in OpenAlex.
- A Personalized Predictor of Motor Imagery Ability Based on Multi-frequency EEG Features.Neuroscience bulletin · 2025Article
- Neurophysiological Approaches to Lie Detection: A Systematic Review.Brain sciences · 2025Review
- The Application of Entropy in Motor Imagery Paradigms of Brain-Computer Interfaces.Brain sciences · 2025Review
- Neurophysiological predictors of deep learning based unilateral upper limb motor imagery classification.Frontiers in human neuroscience · 2025Article
- Integrating fMRI spatial network dynamics and EEG spectral power: insights into resting state connectivity.Frontiers in neuroscience · 2025Article
- The EEG-Based Fusion Entropy-Featured Identification of Isometric Contraction Forces under the Same Action.Sensors (Basel, Switzerland) · 2024Article
- A Multi-Scale Temporal Convolutional Network with Attention Mechanism for Force Level Classification during Motor Imagery of Unilateral Upper-Limb Movements.Entropy (Basel, Switzerland) · 2023Article
- The Electroencephalographic Brainwave Spectrum, Mindful Meditation, and Awareness: Hypothesis.International journal of yogaArticle
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Motor imagery-based brain-computer interfaces (MI-BCIs) have great application prospects in motor enhancement and rehabilitation. However, the capacity to control a MI-BCI varies among persons. Predicting the MI ability of a user remains challenging in BCI studies. We first calculated the relative power level (
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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.