4.8k citations · 4.9k across the 8 of their papers we have counts for
9 papers
2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets
Xiaoxi Wei, A. Aldo Faisal, Moritz Grosse-Wentrup +18
Transfer learning and meta-learning offer some of the most promising avenues to unlock the scalability of healthcare and consumer technologies driven by biosignal data. This is bec…
Collaborative Brain-Computer Interface for Human Interest Detection in Complex and Dynamic Settings
Amelia J. Solon, Stephen M. Gordon, Jonathan R. McDaniel +1
Humans can fluidly adapt their interest in complex environments in ways that machines cannot. Here, we lay the groundwork for a real-world system that passively monitors and merges…
Analyzing P300 Distractors for Target Reconstruction
Jonathan R. McDaniel, Stephen M. Gordon, Amelia J. Solon +1
P300-based brain-computer interfaces (BCIs) are often trained per-user and per-application space. Training such models requires ground truth knowledge of target and non-target stim…
Agreement Rate Initialized Maximum Likelihood Estimator for Ensemble Classifier Aggregation and Its Application in Brain-Computer Interface
Dongrui Wu, Vernon J. Lawhern, Stephen Gordon +2
Ensemble learning is a powerful approach to construct a strong learner from multiple base learners. The most popular way to aggregate an ensemble of classifiers is majority voting,…
Offline EEG-Based Driver Drowsiness Estimation Using Enhanced Batch-Mode Active Learning (EBMAL) for Regression
Dongrui Wu, Vernon J. Lawhern, Stephen Gordon +2
There are many important regression problems in real-world brain-computer interface (BCI) applications, e.g., driver drowsiness estimation from EEG signals. This paper considers of…
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…
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…
EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces
Vernon J. Lawhern, Amelia J. Solon, Nicholas R. Waytowich +3
Brain computer interfaces (BCI) enable direct communication with a computer, using neural activity as the control signal. This neural signal is generally chosen from a variety of w…
A novel method linking neural connectivity to behavioral fluctuations: Behavior-Regressed Connectivity
Antony D. Passaro, Jean M. Vettel, Jonathan McDaniel +3
Background: During an experimental session, behavioral performance fluctuates, yet most neuroimaging analyses of functional connectivity derive a single connectivity pattern. These…