| Deep learning multimodal fNIRS and EEG signals for bimanual grip force decoding P Ortega, AA Faisal Journal of neural engineering 18 (4), 0460e6, 2021 | 25 | 2021 |
| HYGRIP: full-stack characterization of neurobehavioral signals (fNIRS, EEG, EMG, Force, and Breathing) during a bimanual grip force control task P Ortega, T Zhao, AA Faisal Frontiers in Neuroscience 14, 919, 2020 | 18 | 2020 |
| HemCNN: Deep Learning enables decoding of fNIRS cortical signals in hand grip motor tasks P Ortega, A Faisal 2021 10th International IEEE/EMBS Conference on Neural Engineering (NER …, 2021 | 8 | 2021 |
| Compact convolutional neural networks for multi-class, personalised, closed-loop EEG-BCI P Ortega, C Colas, AA Faisal 2018 7th IEEE International Conference on Biomedical Robotics and …, 2018 | 8 | 2018 |
| Deep Real-Time Decoding of bimanual grip force from EEG & fNIRS P Ortega, T Zhao, A Faisal 2021 10th International IEEE/EMBS Conference on Neural Engineering (NER …, 2021 | | 2021 |
| Optimal identification of the hemodynamic response under non-stationary conditions P Ortega, AA Faisal UK Sensorimotor Conference, 2019 | | 2019 |
| Mutually informed dynamical models for fNIRS denoising based on EMG and EEG P Ortega, AA Faisal Annual Conference of the Society for Neuroscience 225 (16), 2018 | | 2018 |
| Directed information relationship between EMG, EEG and fNIRS during isometric hand contractions P Ortega, AA Faisal Annual Conference of the Society for the Neural Control of Movement, 2018 | | 2018 |
| Convolutional Neural Networks for raw EEG time series classification P Ortega, C Colas, C Konnaris, I Radcliff, AA Faisal 1st Cybathlon Symposium, 2016 | | 2016 |
A. Aldo FaisalProfessor in AI & Neuroscience, Imperial College; Chair in Digital Health, University of BayreuthVerified email at imperial.ac.uk
