ECoG Real Time Signal Processing for Clinical Self paced BCI Application

Nana Arizumi, Guillaume Charvet, Andrey Eliseyev, Jérémy Pradal, Serpil Cokgungor, Nicolas Tarrin, Corinne Mestais, Tetiana Aksenova, Alim-Louis Benabid

2013

Abstract

The overall goal of the Brain Computer Interface (BCI) project led at CEA/LETI/CLINATEC® is to improve the quality of life of quadriplegic subjects. BCI will allow them to control effectors such as an exoskeleton, through recording and processing of the electrical activity of their brain. To do this, a wireless 64-channel ElectroCorticoGram (ECoG) recording device WIMAGINE® (Wireless Implantable Multi-channel Acquisition system for Generic Interface with NEurons) has been designed for long-term human implantation to interface an electrode array to an external computer. To decode the ECoG data, high resolution algorithm has been constructed at CLINATEC®. Once the data are treated, they are used to control the external effectors. To reach the overall goal, it is crucial to construct a whole software system working in real time. In order to prepare the BCI software system for the clinical trials, we demonstrated online real time Electrocorticogram (ECoG) signal processing using Monkey ECoG recordings corresponding to an arm movement. The algorithm of N-way Partial Least Square (NPLS) regression family is applied to extract linear model from the recordings. The model is used to control the robotic arm JACO (KINOVA) as a demonstrator.

References

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Paper Citation


in Harvard Style

Arizumi N., Charvet G., Eliseyev A., Pradal J., Cokgungor S., Tarrin N., Mestais C., Aksenova T. and Benabid A. (2013). ECoG Real Time Signal Processing for Clinical Self paced BCI Application . In - BrainRehab, (NEUROTECHNIX 2013) ISBN , pages 0-0


in Bibtex Style

@conference{brainrehab13,
author={Nana Arizumi and Guillaume Charvet and Andrey Eliseyev and Jérémy Pradal and Serpil Cokgungor and Nicolas Tarrin and Corinne Mestais and Tetiana Aksenova and Alim-Louis Benabid},
title={ECoG Real Time Signal Processing for Clinical Self paced BCI Application},
booktitle={ - BrainRehab, (NEUROTECHNIX 2013)},
year={2013},
pages={},
publisher={SciTePress},
organization={INSTICC},
doi={},
isbn={},
}


in EndNote Style

TY - CONF
JO - - BrainRehab, (NEUROTECHNIX 2013)
TI - ECoG Real Time Signal Processing for Clinical Self paced BCI Application
SN -
AU - Arizumi N.
AU - Charvet G.
AU - Eliseyev A.
AU - Pradal J.
AU - Cokgungor S.
AU - Tarrin N.
AU - Mestais C.
AU - Aksenova T.
AU - Benabid A.
PY - 2013
SP - 0
EP - 0
DO -