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  • 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 in contrast 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.
  • 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 in contrast 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. (en)
Title
  • ssMRP state detection for brain computer interfacing using hidden Markov models
  • ssMRP state detection for brain computer interfacing using hidden Markov models (en)
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  • ssMRP state detection for brain computer interfacing using hidden Markov models
  • ssMRP state detection for brain computer interfacing using hidden Markov models (en)
skos:notation
  • RIV/68407700:21230/09:00158093!RIV10-MSM-21230___
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  • Z(MSM6840770012)
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  • 343274
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  • RIV/68407700:21230/09:00158093
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  • ssMRP; HMM; EEG; Brain Computer Interface (en)
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http://linked.open...ontrolniKodProRIV
  • [C99925DFC631]
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  • Cardiff
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  • New York
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  • Proceedings of the Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on
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  • Šťastný, Jakub
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number of pages
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  • IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
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  • 978-1-4244-2709-3
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  • 21230
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