Deep learning-based classification for brain-computer interfaces
Explore this paper's citation graph
- Type
- article
- Published
- 2017-10-01
- Cited by
- 79
- References
- 36
- OpenAlex
- https://openalex.org/W2772472921
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:33682292
Keywords
Computer science, Artificial intelligence, Deep learning, Support vector machine, Brain–computer interface
References
- Comparative analysis of strategies for feature extraction and classification in SSVEP BCIs
- Brain computer interfacing: Applications and challenges
- Multi-class AdaBoost ∗
- A novel BCI-SSVEP based approach for control of walking in Virtual Environment using a Convolutional Neural Network
- Real-time ocular artifact suppression using recurrent neural network for electro-encephalogram based brain-computer interface
- Support vector machines
- A Learning Algorithm for Continually Running Fully Recurrent Neural Networks
- A brain-computer interface (BCI) for the locked-in: comparison of different EEG classifications for the thought translation device.
- Long Short-Term Memory
- A Direct Method of Nonparametric Measurement Selection
- A review of classification algorithms for EEG-based brain–computer interfaces
- K-nearest neighbor
- C4.5: Programs for Machine Learning
- Classification of EEG during imagined mental tasks by forecasting with Elman Recurrent Neural Networks
- Convolutional Neural Networks for P300 Detection with Application to Brain-Computer Interfaces
- Convolutional Neural Network with embedded Fourier Transform for EEG classification
- ImageNet classification with deep convolutional neural networks
- A comparison of classification techniques for the P300 Speller
- Comparative evaluation of state-of-the-art algorithms for SSVEP-based BCIs
- TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Cited by
- On-board brain-computer interface based on the recognition of patterns of brain activity through a convolutional neural network
- On the Classification of SSVEP-Based Dry-EEG Signals via Convolutional Neural Networks
- Validating Deep Neural Networks for Online Decoding of Motor Imagery Movements from EEG Signals
- Deep Fusion Feature Learning Network for MI-EEG Classification
- A Frequency Domain Classifier of Steady-State Visual Evoked Potentials Using Deep Separable Convolutional Neural Networks
- World’s fastest brain-computer interface: Combining EEG2Code with deep learning
- Simulating Brain Signals: Creating Synthetic EEG Data via Neural-Based Generative Models for Improved SSVEP Classification
- Augmentative and Alternative Communication (AAC) Advances: A Review of Configurations for Individuals with a Speech Disability
- Towards Control of EEG-Based Robotic Arm Using Deep Learning via Stacked Sparse Autoencoder
- A Feature Extraction Method Based on Differential Entropy and Linear Discriminant Analysis for Emotion Recognition
- Deep Learning in the Biomedical Applications: Recent and Future Status
- Motor Imagery EEG Classification Using Capsule Networks
- Protocol for Controlling Fan Speed in Real Time via Brain Waves
- Mobile Switch Control Using Auditory and Haptic Steady State Response in Ear-EEG
- Motor Imagery EEG Signals Classification Based on Mode Amplitude and Frequency Components Using Empirical Wavelet Transform
- Decoding SSVEP on time and frequency domain using Convolutional Neural Network
- Decoding of visual-related information from the human EEG using an end-to-end deep learning approach
- LSTM-based Classification of Multiflicker-SSVEP in Single Channel Dry-EEG for Low-power/High-accuracy Quadcopter-BMI System
- Towards a home-use BCI: fast asynchronous control and robust non-control state detection
- EEG-Based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and Their Applications
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