ssMRP state detection for brain computer interfacing using hidden Markov models

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F09%3A00158093" target="_blank" >RIV/68407700:21230/09:00158093 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

ssMRP state detection for brain computer interfacing using hidden Markov models

Original language description

This paper reports preliminary results of steady-state movement related potential (ssMRP) classification using hidden Markov models (HMM). We develop a HMM-based classifier for a three-class BCI problem, i.e. rest, left/right finger tapping. Note that incontrast to [1], we here experimentally select the best pair of channels which attain the highest classification score instead of the 45 electrodes all over the sensorimotor cortex. The averaged correct classification rates (CCR) for different sliding time windows are reported. Reliable single trial classification rates of approximately 60%-80% accuracy are achievable.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

JC - Computer hardware and software

OECD FORD branch

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Project

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2009

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on

ISBN

978-1-4244-2709-3

ISSN

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e-ISSN

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Number of pages

4

Pages from-to

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Publisher name

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

Place of publication

New York

Event location

Cardiff

Event date

Aug 31, 2009

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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