ArticlePloS one2020
Mu-Beta event-related (de)synchronization and EEG classification of left-right foot dorsiflexion kinaesthetic motor imagery for BCI.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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19 citing papers in PubMed, 58 citations in OpenAlex.
- Assessing Motor Cortical Activity: How Repetitions Impact Motor Execution and Imagery Analysis.Psychophysiology · 2025Article
- The Application of Entropy in Motor Imagery Paradigms of Brain-Computer Interfaces.Brain sciences · 2025Review
- AMEEGNet: attention-based multiscale EEGNet for effective motor imagery EEG decoding.Frontiers in neurorobotics · 2025Article
- Utilizing statistical analysis for motion imagination classification in brain-computer interface systems.PloS one · 2025Article
- Decoding lower-limb kinematic parameters during pedaling tasks using deep learning approaches and EEG.Medical & biological engineering & computing · 2024Article
- A Method for the Spatial Interpolation of EEG Signals Based on the Bidirectional Long Short-Term Memory Network.Sensors (Basel, Switzerland) · 2024Article
- Source-Based EEG Neurofeedback for Sustained Motor Imagery of a Single Leg.Sensors (Basel, Switzerland) · 2023Article
- Review of adaptive control for stroke lower limb exoskeleton rehabilitation robot based on motion intention recognition.Frontiers in neurorobotics · 2023Review
- Enhanced lower-limb motor imagery by kinesthetic illusion.Frontiers in neuroscience · 2023Article
- Activation Patterns of Functional Brain Network in Response to Action Observation-Induced and Non-Induced Motor Imagery of Swallowing: A Pilot Study.Brain sciences · 2022Article
- Article
- [Progress of classification algorithms for motor imagery electroencephalogram signals].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2021Article
- Effective Connectivity for Decoding Electroencephalographic Motor Imagery Using a Probabilistic Neural Network.Sensors (Basel, Switzerland) · 2021Article
- [Execution, assessment and improvement methods of motor imagery for brain-computer interface].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2021Article
- Identification of Brain Electrical Activity Related to Head Yaw Rotations.Sensors (Basel, Switzerland) · 2021Article
- Development of a Guidance System for Motor Imagery Enhancement Using the Virtual Hand Illusion.Sensors (Basel, Switzerland) · 2021Article
- Enhancement of Event-Related Desynchronization in Motor Imagery Based on Transcranial Electrical Stimulation.Frontiers in human neuroscience · 2021Article
- Developing a Motor Imagery-Based Real-Time Asynchronous Hybrid BCI Controller for a Lower-Limb Exoskeleton.Sensors (Basel, Switzerland) · 2020Article
- Mirror therapy combined with defecation motor imagery and repetitive transcranial magnetic stimulation improves post-stroke constipation: a retrospective study with EEG biomarker analysis.Frontiers in neurologyArticle
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Authors and funding
3 authors at 1 institution in 1 country.
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Abstract
The left and right foot representation area is located within the interhemispheric fissure of the sensorimotor cortex and share spatial proximity. This makes it difficult to visualize the cortical lateralization of event-related (de)synchronization (ERD/ERS) during left and right foot motor imageries. The aim of this study is to investigate the possibility of using ERD/ERS in the mu, low beta, and high beta bandwidth, during left and right foot dorsiflexion kinaesthetic motor imageries (KMI), as unilateral control commands for a brain-computer interface (BCI). EEG was recorded from nine healthy participants during cue-based left-right foot dorsiflexion KMI tasks. The features were analysed for common average and bipolar references. With each reference, mu and beta band-power features were analysed using time-frequency (TF) maps, scalp topographies, and average time course for ERD/ERS. The cortical lateralization of ERD/ERS, during left and right foot KMI, was confirmed. Statistically significant features were classified using LDA, SVM, and KNN model, and evaluated using the area under ROC curves. An increase in high beta power following the end of KMI for both tasks was recorded, from right and left hemispheres, respectively, at the vertex. The single trial analysis and classification models resulted in high discrimination accuracies, i.e. maximum 83.4% for beta ERS, 79.1% for beta ERD, and 74.0% for mu ERD. With each model the features performed above the statistical chance level of 2-class discrimination for a BCI. Our findings indicate these features can evoke left-right differences in single EEG trials. This suggests that any BCI employing unilateral foot KMI can attain classification accuracy suitable for practical implementation. Given results stipulate the novel utilization of mu and beta as independent control features for discrimination of bilateral foot KMI in a BCI.
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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.