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Output details

15 - General Engineering

Imperial College London

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Output 82 of 109 in the submission

Article title

Prediction of arm movement trajectories from ECoG-recordings in humans.

Type

D - Journal article

DOI

10.1016/j.jneumeth.2007.10.001

Title of journal

Journal of Neuroscience Methods

Article number

Volume number

167

Issue number

First page of article

105

ISSN of journal

0165-0270

Year of publication

2008

URL

Number of additional authors

Additional information

Here, we pioneered a novel brain-machine interface (BMI) technology, based on recording neuronal signals directly at the surface of the human brain (Patent DE102006008501.9 25/01/2008). This eliminates the problem of the highly invasive nature of previous brain sensors for BMIs while maintaining high bandwidth, resolution and information. Since our article, epicortical recording has become an influential major technique in BMI research, with about 100 full papers published. I have been invited to several major conferences (eg “BNA2013: Festival of Neuroscience”) to give talks about this research. Our paper has received the “Top cited article award 2008-2010” from the journal.

Interdisciplinary

Yes

Cross-referral requested

Research group

None

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract