Jeremy Hill
homepage: | http://www.kyb.mpg.de/~jez |
search externally: | Google Scholar, Springer, CiteSeer, Microsoft Academic Search, Scirus , DBlife |
Description
His principal interest is in applying machine-learning methods to the development of brain-computer interfaces (BCI). This involves the classification of a user's intentions or mental states, or regression against some continuous intentional control signal, using brain signals obtained for example by EEG, ECoG or MEG. The long-term aim is to develop systems that a completely paralysed person (such as someone suffering from advanced amyotrophic lateral sclerosis) could use to communicate. He is currently pursuing some of these questions in collaboration with Dr. Jason Farquhar, Prof. Peter Desain and others at the Donders Centre for Brain, Cognition and Behaviour in Nijmegen.
Lectures:
lecture Machine Learning for Brain-Computer Interfaces as author at Mini Symposia, 8318 views |
lecture BCPy2000 as author at NIPS Workshop on Machine Learning Open Source Software, Whistler 2008, 8017 views |
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lecture New BCI approaches: Selective Attention to Auditory and Tactile Stimulus Streams as author at Workshop on Methods of Data Analysis in Computational Neuroscience and Brain Computer Interfaces, Berlin 2007, 5583 views |