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EEG oscillatory patterns and classification of sequential compound limb motor imagery

BACKGROUND: A number of studies have been done on movement imagination of motor sequences with a single limb. However, brain oscillatory patterns induced by movement imagination of motor sequences involving multiple limbs have not been reported in recent years. The goal of the present study was to v...

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Autores principales: Yi, Weibo, Qiu, Shuang, Wang, Kun, Qi, Hongzhi, He, Feng, Zhou, Peng, Zhang, Lixin, Ming, Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4731999/
https://www.ncbi.nlm.nih.gov/pubmed/26822435
http://dx.doi.org/10.1186/s12984-016-0119-8
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author Yi, Weibo
Qiu, Shuang
Wang, Kun
Qi, Hongzhi
He, Feng
Zhou, Peng
Zhang, Lixin
Ming, Dong
author_facet Yi, Weibo
Qiu, Shuang
Wang, Kun
Qi, Hongzhi
He, Feng
Zhou, Peng
Zhang, Lixin
Ming, Dong
author_sort Yi, Weibo
collection PubMed
description BACKGROUND: A number of studies have been done on movement imagination of motor sequences with a single limb. However, brain oscillatory patterns induced by movement imagination of motor sequences involving multiple limbs have not been reported in recent years. The goal of the present study was to verify the feasibility of application of motor sequences involving multiple limbs to brain-computer interface (BCI) systems based on motor imagery (MI). The changes of EEG patterns and the inter-influence between movements associated with the imagination of motor sequences were also investigated. METHODS: The experiment, where 12 healthy subjects participated, involved one motor sequence with a single limb and three kinds of motor sequences with two or three limbs. The activity involved mental simulation, imagining playing drums with two conditions (60 and 30 beats per minute for the first and second conditions, respectively). RESULTS: Movement imagination of different limbs in the sequence contributed to time-variant event-related desynchronization (ERD) patterns within both mu and beta rhythms, which was more obvious for the second condition compared with the first condition. The ERD values of left/right hand imagery with prior hand imagery were significantly larger than those with prior foot imagery, while the phase locking values (PLVs) between central electrodes and the mesial frontocentral electrode of non-initial movement were significantly larger than those of the initial movement during imagination of motor sequences for both conditions. Classification results showed that the power spectral density (PSD) based method outperformed the multi-class common spatial patterns (multi-CSP) based method: The highest accuracies were 82.86 % and 91.43 %, and the mean values were 65 % and 74.14 % for the first and second conditions, respectively. CONCLUSIONS: This work implies that motor sequences involving multiple limbs can be utilized to build a multimodal classification paradigm in MI-based BCI systems, and that prior movement imagination can result in the changes of neural activities in motor areas during subsequent movement imagination in the process of limb switching.
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spelling pubmed-47319992016-01-30 EEG oscillatory patterns and classification of sequential compound limb motor imagery Yi, Weibo Qiu, Shuang Wang, Kun Qi, Hongzhi He, Feng Zhou, Peng Zhang, Lixin Ming, Dong J Neuroeng Rehabil Research BACKGROUND: A number of studies have been done on movement imagination of motor sequences with a single limb. However, brain oscillatory patterns induced by movement imagination of motor sequences involving multiple limbs have not been reported in recent years. The goal of the present study was to verify the feasibility of application of motor sequences involving multiple limbs to brain-computer interface (BCI) systems based on motor imagery (MI). The changes of EEG patterns and the inter-influence between movements associated with the imagination of motor sequences were also investigated. METHODS: The experiment, where 12 healthy subjects participated, involved one motor sequence with a single limb and three kinds of motor sequences with two or three limbs. The activity involved mental simulation, imagining playing drums with two conditions (60 and 30 beats per minute for the first and second conditions, respectively). RESULTS: Movement imagination of different limbs in the sequence contributed to time-variant event-related desynchronization (ERD) patterns within both mu and beta rhythms, which was more obvious for the second condition compared with the first condition. The ERD values of left/right hand imagery with prior hand imagery were significantly larger than those with prior foot imagery, while the phase locking values (PLVs) between central electrodes and the mesial frontocentral electrode of non-initial movement were significantly larger than those of the initial movement during imagination of motor sequences for both conditions. Classification results showed that the power spectral density (PSD) based method outperformed the multi-class common spatial patterns (multi-CSP) based method: The highest accuracies were 82.86 % and 91.43 %, and the mean values were 65 % and 74.14 % for the first and second conditions, respectively. CONCLUSIONS: This work implies that motor sequences involving multiple limbs can be utilized to build a multimodal classification paradigm in MI-based BCI systems, and that prior movement imagination can result in the changes of neural activities in motor areas during subsequent movement imagination in the process of limb switching. BioMed Central 2016-01-28 /pmc/articles/PMC4731999/ /pubmed/26822435 http://dx.doi.org/10.1186/s12984-016-0119-8 Text en © Yi et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Yi, Weibo
Qiu, Shuang
Wang, Kun
Qi, Hongzhi
He, Feng
Zhou, Peng
Zhang, Lixin
Ming, Dong
EEG oscillatory patterns and classification of sequential compound limb motor imagery
title EEG oscillatory patterns and classification of sequential compound limb motor imagery
title_full EEG oscillatory patterns and classification of sequential compound limb motor imagery
title_fullStr EEG oscillatory patterns and classification of sequential compound limb motor imagery
title_full_unstemmed EEG oscillatory patterns and classification of sequential compound limb motor imagery
title_short EEG oscillatory patterns and classification of sequential compound limb motor imagery
title_sort eeg oscillatory patterns and classification of sequential compound limb motor imagery
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4731999/
https://www.ncbi.nlm.nih.gov/pubmed/26822435
http://dx.doi.org/10.1186/s12984-016-0119-8
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