Brain-Computer Interfaces
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Subject Areas on Research
- A Brain to Spine Interface for Transferring Artificial Sensory Information.
- A Closed Loop Brain-machine Interface for Epilepsy Control Using Dorsal Column Electrical Stimulation.
- A binary method for simple and accurate two-dimensional cursor control from EEG with minimal subject training.
- A brain-computer interface based attention training program for treating attention deficit hyperactivity disorder.
- A brain-computer interface based cognitive training system for healthy elderly: a randomized control pilot study for usability and preliminary efficacy.
- A brain-machine interface enables bimanual arm movements in monkeys.
- A general P300 brain-computer interface presentation paradigm based on performance guided constraints.
- A novel Bayesian framework for discriminative feature extraction in Brain-Computer Interfaces.
- A pilot randomized controlled trial using EEG-based brain-computer interface training for a Chinese-speaking group of healthy elderly.
- Applying dynamic data collection to improve dry electrode system performance for a P300-based brain-computer interface.
- Bayesian approach to dynamically controlling data collection in P300 spellers.
- Brain Gaming: A User's Product Guide for the Clinician.
- Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation.
- Capturing spike train temporal pattern with wavelet average coefficient for brain machine interface.
- Channel selection methods for the P300 Speller.
- Combining multiple features for error detection and its application in brain-computer interface.
- Commanding a Brain-Controlled Wheelchair Using Steady-State Somatosensory Evoked Potentials.
- Computing Arm Movements with a Monkey Brainet.
- Creating a neuroprosthesis for active tactile exploration of textures.
- Cross-subject decoding of eye movement goals from local field potentials.
- Decoding Movements from Cortical Ensemble Activity Using a Long Short-Term Memory Recurrent Network.
- Decoding individual finger movements from one hand using human EEG signals.
- Deep Pinsker and James-Stein Neural Networks for Decoding Motor Intentions From Limited Data.
- EXiO-A Brain-Controlled Lower Limb Exoskeleton for Rhesus Macaques.
- Effectiveness of a Personalized Brain-Computer Interface System for Cognitive Training in Healthy Elderly: A Randomized Controlled Trial.
- Electrophysiological Decoding of Spatial and Color Processing in Human Prefrontal Cortex.
- Evaluating Brain-Computer Interface Performance in an ALS Population: Checkerboard and Color Paradigms.
- Evaluating brain-computer interface performance using color in the P300 checkerboard speller.
- Evaluation of EEG features in decoding individual finger movements from one hand.
- Increasing BCI communication rates with dynamic stopping towards more practical use: an ALS study.
- Independent home use of a brain-computer interface by people with amyotrophic lateral sclerosis.
- Interfacing to the brain's motor decisions.
- Long-Term Training with a Brain-Machine Interface-Based Gait Protocol Induces Partial Neurological Recovery in Paraplegic Patients.
- Long-term Training With a Brain-Machine Interface-Based Gait Protocol Induces Partial Neurological Recovery in Paraplegic Patients.
- Long-term recording reliability of liquid crystal polymer µECoG arrays.
- Low-power hardware implementation of movement decoding for brain computer interface with reduced-resolution discrete cosine transform.
- Minimax-optimal decoding of movement goals from local field potentials using complex spectral features.
- Mitigating the Impact of Psychophysical Effects During Adaptive Stimulus Selection in the P300 Speller Brain-Computer Interface.
- Moving Away From Error-Related Potentials to Achieve Spelling Correction in P300 Spellers.
- Mutual Information-Driven Subject-Invariant and Class-Relevant Deep Representation Learning in BCI.
- Neuroengineering challenges of fusing robotics and neuroscience.
- Neuroprosthetic decoder training as imitation learning
- Noninvasive brain-computer interface enables communication after brainstem stroke.
- Optimizing the stimulus presentation paradigm design for the P300-based brain-computer interface using performance prediction.
- Place Cell-Like Activity in the Primary Sensorimotor and Premotor Cortex During Monkey Whole-Body Navigation.
- Predicting BCI subject performance using probabilistic spatio-temporal filters.
- Projected accuracy metric for the P300 Speller.
- Regenerative scaffold electrodes for peripheral nerve interfacing.
- Relationship between intracortical electrode design and chronic recording function
- Semi-supervised generative and discriminative adversarial learning for motor imagery-based brain-computer interface.
- Spatiotemporal compression for efficient storage and transmission of high-resolution electrocorticography data.
- The Continuity of BCI-Mediated and Conventional Action.
- Towards a naturalistic brain-machine interface: hybrid torque and position control allows generalization to novel dynamics.
- Training with brain-machine interfaces, visuo-tactile feedback and assisted locomotion improves sensorimotor, visceral, and psychological signs in chronic paraplegic patients.
- Training with noninvasive brain-machine interface, tactile feedback, and locomotion to enhance neurological recovery in individuals with complete paraplegia: a randomized pilot study.
- Using the detectability index to predict P300 speller performance.
- Utilizing a language model to improve online dynamic data collection in P300 spellers.
- Wireless Cortical Brain-Machine Interface for Whole-Body Navigation in Primates.
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Keywords of People
- Abd-El-Barr, Muhammad, Associate Professor of Neurosurgery, Neurosurgery
- Mainsah, Boyla Octavie, Assistant Research Professor in the Department of Electrical and Computer Engineering, Electrical and Computer Engineering
- Nicolelis, Miguel Angelo L., Professor Emeritus of Neurobiology, Neurobiology
- Xiao, Ran, Assistant Consulting Professor in the School of Nursing, School of Nursing