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Post-stroke aphasia rehabilitation using an adapted visual P300 brain-computer interface training: improvement over time, but specificity remains undetermined

Frontiers in human neuroscience, 2024-05, Vol.18, p.1400336

2024

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Inconclusive results of slow cortical potential neurofeedback for the treatment of chronic post-stroke attention deficits

Frontiers in human neuroscience, 2024-04, Vol.18, p.1301622-1301622

2024

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The influence of motivation and emotion on sensorimotor rhythm‐based brain–computer interface performance

Psychophysiology, 2021-08, Vol.58 (8), p.e13832-n/a

2021

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The user-centered design as novel perspective for evaluating the usability of BCI-controlled applications

PloS one, 2014-12, Vol.9 (12), p.e112392-e112392

2014

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P300 brain computer interface: current challenges and emerging trends

Frontiers in neuroengineering, 2012, Vol.5, p.14-14

2012

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Empathy, motivation, and P300 BCI performance

Frontiers in human neuroscience, 2013-10, Vol.7, p.642-642

2013

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Neurofeedback therapy to improve cognitive function in patients with chronic post-stroke attention deficits: a within-subjects comparison

Frontiers in human neuroscience, 2023-07, Vol.17, p.1155584-1155584

2023

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Toward a P300 Based Brain-Computer Interface for Aphasia Rehabilitation after Stroke: Presentation of Theoretical Considerations and a Pilot Feasibility Study

Frontiers in human neuroscience, 2016-11, Vol.10, p.547

2016

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Psychological Predictors of Visual and Auditory P300 Brain-Computer Interface Performance

Frontiers in neuroscience, 2018-05, Vol.12, p.307-307

2018

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Visuo-motor coordination ability predicts performance with brain-computer interfaces controlled by modulation of sensorimotor rhythms (SMR)

Frontiers in human neuroscience, 2014-08, Vol.8, p.574-574

2014

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Brain Painting: First Evaluation of a New Brain-Computer Interface Application with ALS-Patients and Healthy Volunteers

Frontiers in neuroscience, 2010-01, Vol.4, p.182-182

2010

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The WIN-speller: a new intuitive auditory brain-computer interface spelling application

Frontiers in neuroscience, 2015-10, Vol.9, p.346-346

2015

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Brain Painting: Usability testing according to the user-centered design in end users with severe motor paralysis

Artificial intelligence in medicine, 2013-10, Vol.59 (2), p.99-110

2013

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Probing command following in patients with disorders of consciousness using a brain–computer interface

Clinical neurophysiology, 2013-01, Vol.124 (1), p.101-106

2013

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Psychological Factors Influencing Brain-Computer Interface (BCI) Performance

2015 IEEE International Conference on Systems, Man, and Cybernetics, 2015, p.3192-3196

2015

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Out of the frying pan into the fire—the P300-based BCI faces real-world challenges

Brain Machine Interfaces, 2011, Vol.194, p.27-46

2011

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Psychological Perspectives: Quality of Life and Motivation

Brain-Computer-Interfaces in their ethical, social and cultural contexts, p.77-84

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Improving EEG-BCI analysis for low certainty subjects by using dictionary learning

2015 20th Symposium on Signal Processing, Images and Computer Vision (STSIVA), 2015, p.1-7

2015

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Brain–Computer Interfaces and Assistive Technology

Brain-Computer-Interfaces in their ethical, social and cultural contexts, p.7-38

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Does mastery confidence influence P300 based brain-computer interface (BCI) performance?

2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2016, p.001433-001436

2016

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Why User-Centered Design Is Relevant for Brain–Computer Interfacing and How It Can Be Implemented in Study Protocols

Brain–Computer Interfaces Handbook, 2018, Vol.1, p.585-594

1, 2018

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Brain–Computer Interfaces: Effects on Brain Activation and Behavior

Neuroadaptive Systems, 2013, p.217-252

2013

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Post-stroke aphasia rehabilitation using an adapted visual P300 brain-computer interface training: improvement over time, but specificity remains undetermined

Inconclusive results of slow cortical potential neurofeedback for the treatment of chronic post-stroke attention deficits

The influence of motivation and emotion on sensorimotor rhythm‐based brain–computer interface performance

The user-centered design as novel perspective for evaluating the usability of BCI-controlled applications

P300 brain computer interface: current challenges and emerging trends

Empathy, motivation, and P300 BCI performance

Neurofeedback therapy to improve cognitive function in patients with chronic post-stroke attention deficits: a within-subjects comparison

Toward a P300 Based Brain-Computer Interface for Aphasia Rehabilitation after Stroke: Presentation of Theoretical Considerations and a Pilot Feasibility Study

Psychological Predictors of Visual and Auditory P300 Brain-Computer Interface Performance

Visuo-motor coordination ability predicts performance with brain-computer interfaces controlled by modulation of sensorimotor rhythms (SMR)

Brain Painting: First Evaluation of a New Brain-Computer Interface Application with ALS-Patients and Healthy Volunteers

The WIN-speller: a new intuitive auditory brain-computer interface spelling application

Brain Painting: Usability testing according to the user-centered design in end users with severe motor paralysis

Probing command following in patients with disorders of consciousness using a brain–computer interface

Psychological Factors Influencing Brain-Computer Interface (BCI) Performance

Out of the frying pan into the fire—the P300-based BCI faces real-world challenges

Psychological Perspectives: Quality of Life and Motivation

Improving EEG-BCI analysis for low certainty subjects by using dictionary learning

Brain–Computer Interfaces and Assistive Technology

Does mastery confidence influence P300 based brain-computer interface (BCI) performance?

Why User-Centered Design Is Relevant for Brain–Computer Interfacing and How It Can Be Implemented in Study Protocols

Brain–Computer Interfaces: Effects on Brain Activation and Behavior

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