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EEG-Based User Reaction Time Estimation Using Riemannian Geometry Features
Dongrui Wu, Brent J. Lance, Vernon J. Lawhern +3
Riemannian geometry has been successfully used in many brain-computer interface (BCI) classification problems and demonstrated superior performance. In this paper, for the first ti…
Spatial Filtering for EEG-Based Regression Problems in Brain-Computer Interface (BCI)
Dongrui Wu, Jung-Tai King, Chun-Hsiang Chuang +2
Electroencephalogram (EEG) signals are frequently used in brain-computer interfaces (BCIs), but they are easily contaminated by artifacts and noises, so preprocessing must be done…
Switching EEG Headsets Made Easy: Reducing Offline Calibration Effort Using Active Weighted Adaptation Regularization
Dongrui Wu, Vernon J. Lawhern, W. David Hairston +1
Electroencephalography (EEG) headsets are the most commonly used sensing devices for Brain-Computer Interface. In real-world applications, there are advantages to extrapolating dat…
Driver Drowsiness Estimation from EEG Signals Using Online Weighted Adaptation Regularization for Regression (OwARR)
Dongrui Wu, Vernon J. Lawhern, Stephen Gordon +2
One big challenge that hinders the transition of brain-computer interfaces (BCIs) from laboratory settings to real-life applications is the availability of high-performance and rob…
Online and Offline Domain Adaptation for Reducing BCI Calibration Effort
Dongrui Wu
Many real-world brain-computer interface (BCI) applications rely on single-trial classification of event-related potentials (ERPs) in EEG signals. However, because different subjec…