ArticleFrontiers in neuroinformatics2018
Most Popular Signal Processing Methods in Motor-Imagery BCI: A Review and Meta-Analysis.
Article in Frontiers in neuroinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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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.
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Who cites it
33 citing papers in PubMed.
- Subject-Specific Deep Learning Model for Motor Imagery Direction Decoding.Sensors (Basel, Switzerland) · 2026Article
- Characterization of error-related potentials during the command of a lower-limb exoskeleton based on deep learning.Journal of neuroengineering and rehabilitation · 2025Article
- MCTGNet: A Multi-Scale Convolution and Hybrid Attention Network for Robust Motor Imagery EEG Decoding.Bioengineering (Basel, Switzerland) · 2025Article
- A review of hybrid EEG-based multimodal human-computer interfaces using deep learning: applications, advances, and challenges.Biomedical engineering letters · 2025Review
- A comprehensive study of template-based frequency detection methods in SSVEP-based brain-computer interfaces.Behavior research methods · 2025Article
- Time-Frequency Analysis of Motor Imagery During Plantar and Dorsal Flexion Movements Using a Low-Cost Ankle Exoskeleton.Sensors (Basel, Switzerland) · 2025Article
- Single-Trial Electroencephalography Discrimination of Real, Regulated, Isometric Wrist Extension and Wrist Flexion.Biomimetics (Basel, Switzerland) · 2025Article
- Optimizing Real-Time MI-BCI Performance in Post-Stroke Patients: Impact of Time Window Duration on Classification Accuracy and Responsiveness.Sensors (Basel, Switzerland) · 2024Article
- Low-Cost Dynamometer for Measuring and Regulating Wrist Extension and Flexion Motor Tasks in Electroencephalography Experiments.Sensors (Basel, Switzerland) · 2024Article
- Brain-machine interface based on deep learning to control asynchronously a lower-limb robotic exoskeleton: a case-of-study.Journal of neuroengineering and rehabilitation · 2024Article
- Article
- Evaluating the Feasibility of Visual Imagery for an EEG-Based Brain-Computer Interface.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2024Article
- Brain-machine interface based on transfer-learning for detecting the appearance of obstacles during exoskeleton-assisted walking.Frontiers in neuroscience · 2023Article
- Predicting motor behavior: an efficient EEG signal processing pipeline to detect brain states with potential therapeutic relevance for VR-based neurorehabilitation.Virtual reality · 2023Article
- A case for hybrid BCIs: combining optical and electrical modalities improves accuracy.Frontiers in human neuroscience · 2023Article
- Effects of handedness on brain oscillatory activity during imagery and execution of upper limb movements.Frontiers in psychology · 2023Article
- Analyzing and computing humans by means of the brain using Brain-Computer Interfaces - understanding the user - previous evidence, self-relevance and the user's self-concept as potential superordinate human factors of relevance.Frontiers in human neuroscience · 2023Review
- Writing Blindly in Incomplete Locked-In Syndrome with A Custom-Made Switch-Operated Voice-Scanning Communicator-A Case Report.Brain sciences · 2022Article
- Language Model-Guided Classifier Adaptation for Brain-Computer Interfaces for Communication.Conference proceedings. IEEE International Conference on Systems, Man, and Cybernetics · 2022Article
- Coefficient-of-variation-based channel selection with a new testing framework for MI-based BCI.Cognitive neurodynamics · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Brain-Computer Interfaces (BCI) constitute an alternative channel of communication between humans and environment. There are a number of different technologies which enable the recording of brain activity. One of these is electroencephalography (EEG). The most common EEG methods include interfaces whose operation is based on changes in the activity of Sensorimotor Rhythms (SMR) during imagery movement, so-called Motor Imagery BCI (MIBCI).The present article is a review of 131 articles published from 1997 to 2017 discussing various procedures of data processing in MIBCI. The experiments described in these publications have been compared in terms of the methods used for data registration and analysis. Some of the studies (76 reports) were subjected to meta-analysis which showed corrected average classification accuracy achieved in these studies at the level of 51.96%, a high degree of heterogeneity of results (
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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.