| Decoding Imagined, Heard, and Spoken Speech: Classification and Regression of EEG Using a 14-Channel Dry-Contact Mobile Headset. J Clayton, S Wellington, C Valentini-Botinhao, O Watts INTERSPEECH, 4886-4890, 2020 | 13 | 2020 |
| Decoding continuous kinetic information of grasp from stereo-electroencephalographic (SEEG) recordings X Wu, G Li, S Jiang, S Wellington, S Liu, Z Wu, B Metcalfe, L Chen, ... Journal of Neural Engineering 19 (2), 026047, 2022 | 10 | 2022 |
| Fourteen-channel EEG with Imagined Speech (FEIS) dataset S Wellington, J Clayton University of Edinburgh, 2019 | 5 | 2019 |
| Bimodal electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition FS Liwicki, V Gupta, R Saini, K De, N Abid, S Rakesh, S Wellington, ... bioRxiv, 2022.05. 24.492109, 2022 | 3* | 2022 |
| Performance of data-driven inner speech decoding with same-task EEG-fMRI data fusion and bimodal models H Wilson, S Wellington, FS Liwicki, V Gupta, R Saini, K De, N Abid, ... arXiv preprint arXiv:2306.10854, 2023 | 1 | 2023 |
| Bimodal pilot study on inner speech decoding reveals the potential of combining EEG and fMRI F Simistira Liwicki, V Gupta, R Saini, K De, N Abid, S Rakesh, ... | | 2022 |
Jonathan A ClaytonUniversity of SheffieldVerified email at sheffield.ac.uk
