Evaluation of Multi-layer Perceptron Neural Networks in Predicting Ankle Dorsiflexion in Healthy Adults using Movement-related Cortical Potentials for BCI-Neurofeedback Applications
Author:
Affiliation:
1. Clinical Center, National Institutes of Health,Functional and Applied Biomechanics Section of the Rehabilitation Medicine Department,Bethesda,MD,USA,20892
Funder
NIH Clinical Center
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9896400/9896402/09896584.pdf?arnumber=9896584
Reference16 articles.
1. Classification of Hand Movements From EEG Using a Deep Attention-Based LSTM Network
2. Brain Computer Interface for Neuro-rehabilitation With Deep Learning Classification and Virtual Reality Feedback
3. Deep Neural Network for Visual Stimulus-Based Reaction Time Estimation Using the Periodogram of Single-Trial EEG
4. Optimal spatial filtering of single trial EEG during imagined hand movement
5. Spatial filter selection for EEG-based communication
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1. Development and evaluation of a BCI-neurofeedback system with real-time EEG detection and electrical stimulation assistance during motor attempt for neurorehabilitation of children with cerebral palsy;Frontiers in Human Neuroscience;2024-04-03
2. Non-Linear Adapted Spatio-Temporal Filter for Single-Trial Identification of Movement-Related Cortical Potential;Electronics;2023-03-05
3. Computer-Aided Ankle Ligament Injury Diagnosis from Magnetic Resonance Images Using Machine Learning Techniques;Sensors;2023-02-01
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