EEG-Based Motor Imagery BCI Algorithms and Technologies: A Review

arXiv:2609.32930 · eess.SP, cs.LG · Submitted 2026-09-26 · Read on arXiv

eess.SP, cs.LG

Submitted: 2026-09-26

Updated: 2026-09-26

Terminology

• Motor Imagery — 159× in this paper
• Feature Extraction — 45× in this paper · explained in 2 episodes
• Robustness — 31× in this paper · explained in 5 episodes
• Accuracy — 25× in this paper · explained in 1 episode
• Transformer — 20× in this paper · explained in 2 episodes
• Generalization — 16× in this paper · explained in 13 episodes
• Feature Selection — 14× in this paper · explained in 4 episodes
• Adaptation — 11× in this paper · explained in 1 episode
• Benchmark — 11× in this paper · explained in 2 episodes
• Transfer Learning — 10× in this paper · explained in 10 episodes
• Calibration — 8× in this paper · explained in 7 episodes
• Core — 8× in this paper · explained in 2 episodes
• Edge Processing — 8× in this paper
• Sparsity — 8× in this paper · explained in 4 episodes
• fNIRS — 8× in this paper · explained in 2 episodes
• Generative AI — 7× in this paper · explained in 2 episodes
• Benchmarking — 6× in this paper · explained in 3 episodes
• Domain Adaptation — 6× in this paper · explained in 5 episodes
• Wavelet Transform — 6× in this paper · explained in 2 episodes
• alpha — 6× in this paper · explained in 1 episode
• Activation Function — 5× in this paper · explained in 1 episode
• Internet of Things — 5× in this paper
• Interpretability — 5× in this paper · explained in 15 episodes
• Alignment — 4× in this paper · explained in 1 episode
• Attention Mechanism — 4× in this paper · explained in 2 episodes
• Feature Engineering — 4× in this paper · explained in 3 episodes
• Quantization — 4× in this paper · explained in 12 episodes
• Decode — 3× in this paper · explained in 2 episodes
• Edge AI — 3× in this paper · explained in 2 episodes
• Guided attention — 3× in this paper · explained in 2 episodes
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• AUC — 2× in this paper · explained in 2 episodes
• Chinese Control And Decision Conference — 2× in this paper
• Clustering — 2× in this paper · explained in 2 episodes
• Data Augmentation — 2× in this paper · explained in 7 episodes
• Edge Devices — 2× in this paper · explained in 2 episodes
• Ensemble Learning — 2× in this paper · explained in 2 episodes
• Event-Related Desynchronization — 2× in this paper
• Event-Related Synchronization — 2× in this paper
• Federated Learning — 2× in this paper · explained in 14 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• International Winter Conference on Brain-Computer Interface — 2× in this paper
• Latent Representation — 2× in this paper · explained in 2 episodes
• Non-stationarity — 2× in this paper · explained in 2 episodes
• Personalization — 2× in this paper · explained in 2 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• 1D CNN — 1× in this paper · explained in 2 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Active Learning — 1× in this paper · explained in 6 episodes
• Adaptability — 1× in this paper · explained in 1 episode
• Adaptive Decoding — 1× in this paper · explained in 1 episode
• Affective Computing — 1× in this paper · explained in 1 episode
• Artificial Intelligence (AI) — 1× in this paper · explained in 2 episodes
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Closed-Loop System — 1× in this paper · explained in 4 episodes
• Computational Biology — 1× in this paper · explained in 2 episodes
• Continual Learning — 1× in this paper · explained in 2 episodes
• Convolutional Neural Networks (CNNs) — 1× in this paper · explained in 2 episodes
• Covariate Shift — 1× in this paper · explained in 2 episodes
• Curse of Dimensionality — 1× in this paper · explained in 6 episodes
• Energy Efficiency — 1× in this paper · explained in 3 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Flattening and Fully Connected Layer — 1× in this paper
• Frustration — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Meta-learning — 1× in this paper · explained in 2 episodes
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Online Adaptation — 1× in this paper · explained in 3 episodes
• Paper Review — 1× in this paper · explained in 2 episodes
• Principal Component Analysis (PCA) — 1× in this paper · explained in 4 episodes
• Provenance — 1× in this paper · explained in 3 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Selection Bias — 1× in this paper · explained in 4 episodes
• Self-Supervised Learning — 1× in this paper · explained in 7 episodes
• Semi-supervised Learning — 1× in this paper · explained in 4 episodes
• Signal-to-noise ratio (SNR) — 1× in this paper · explained in 2 episodes
• Standardized Benchmarks — 1× in this paper · explained in 2 episodes
• Steady-state Visual Evoked Potential — 1× in this paper
• System-on-a- Chip — 1× in this paper
• Transformer Models — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes
• Verification — 1× in this paper · explained in 2 episodes
• Wearable Edge Processing on Chip — 1× in this paper

Sources

• Early Prediction of Epilepsy Seizures VLSI BCI System
• An approach to interfacing the brain with quantum computers: practical steps and caveats

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