Semantic brain-computer interfacing
Brain-computer interfaces (BCIs) based on identifying activity in the brain related to semantic concepts have the potential to be highly intuitive and allow greater levels of accuracy and communication speed than possible with current BCIs. I will investigate novel machine learning techniques to develop a new type of semantic BCI based on simultaneous recording of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS).
I defended my PhD thesis Towards EEG/fNIRS-based semantic brain-computer interfacing.
We published our topical review of Neural decoding of semantic concepts: A systematic literature review in the Journal of Neural Engineering 2022.
We published our results to Decode semantic categories of imagined concepts of animals and tools in the recorded brain activity by functional near-infrared spectroscopy (fNIRS) in the Journal of Neural Engineering 2021.
I presented a poster about my ongoing research at ECEM 2019 (Essex Cross-Disciplinary Experimental Methods) Conference held at the University of Essex.