4 citations · 7 across the 5 of their papers we have counts for
5 papers
Towards AI-controlled FES-restoration of arm movements: Controlling for progressive muscular fatigue with Gaussian state-space models
Nat Wannawas, A. Aldo Faisal
Reaching disability limits an individual's ability in performing daily tasks. Surface Functional Electrical Stimulation (FES) offers a non-invasive solution to restore the lost abi…
Federated deep transfer learning for EEG decoding using multiple BCI tasks
Xiaoxi Wei, A. Aldo Faisal
Deep learning has been successful in BCI decoding. However, it is very data-hungry and requires pooling data from multiple sources. EEG data from various sources decrease the decod…
MIDAS: Deep learning human action intention prediction from natural eye movement patterns
Paul Festor, Ali Shafti, Alex Harston +3
Eye movements have long been studied as a window into the attentional mechanisms of the human brain and made accessible as novelty style human-machine interfaces. However, not ever…
CNNATT: Deep EEG & fNIRS Real-Time Decoding of bimanual forces
Pablo Ortega, Tong Zhao, Aldo Faisal
Non-invasive cortical neural interfaces have only achieved modest performance in cortical decoding of limb movements and their forces, compared to invasive brain-computer interface…
Model-Agnostic Meta-Learning for EEG Motor Imagery Decoding in Brain-Computer-Interfacing
Denghao Li, Pablo Ortega, Xiaoxi Wei +1
We introduce here the idea of Meta-Learning for training EEG BCI decoders. Meta-Learning is a way of training machine learning systems so they learn to learn. We apply here meta-le…