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Bimodal Data Fusion of Simultaneous Measurements of EEG and fNIRS during Lower Limb Movements
Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have temporal and spatial characteristics that may complement each other and, therefore, pose an intriguing approach for brain-computer interaction (BCI). In this work, the relationship between the hemodynamic response an...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8227788/ https://www.ncbi.nlm.nih.gov/pubmed/34071982 http://dx.doi.org/10.3390/brainsci11060713 |
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author | AL-Quraishi, Maged S. Elamvazuthi, Irraivan Tang, Tong Boon Al-Qurishi, Muhammad Adil, Syed Hasan Ebrahim, Mansoor |
author_facet | AL-Quraishi, Maged S. Elamvazuthi, Irraivan Tang, Tong Boon Al-Qurishi, Muhammad Adil, Syed Hasan Ebrahim, Mansoor |
author_sort | AL-Quraishi, Maged S. |
collection | PubMed |
description | Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have temporal and spatial characteristics that may complement each other and, therefore, pose an intriguing approach for brain-computer interaction (BCI). In this work, the relationship between the hemodynamic response and brain oscillation activity was investigated using the concurrent recording of fNIRS and EEG during ankle joint movements. Twenty subjects participated in this experiment. The EEG was recorded using 20 electrodes and hemodynamic responses were recorded using 32 optodes positioned over the motor cortex areas. The event-related desynchronization (ERD) feature was extracted from the EEG signal in the alpha band (8–11) Hz, and the concentration change of the oxy-hemoglobin (oxyHb) was evaluated from the hemodynamics response. During the motor execution of the ankle joint movements, a decrease in the alpha (8–11) Hz amplitude (desynchronization) was found to be correlated with an increase of the oxyHb (r = −0.64061, p < 0.00001) observed on the Cz electrode and the average of the fNIRS channels (ch28, ch25, ch32, ch35) close to the foot area representation. Then, the correlated channels in both modalities were used for ankle joint movement classification. The result demonstrates that the integrated modality based on the correlated channels provides a substantial enhancement in ankle joint classification accuracy of 93.01 ± 5.60% (p < 0.01) compared with single modality. These results highlight the potential of the bimodal fNIR–EEG approach for the development of future BCI for lower limb rehabilitation. |
format | Online Article Text |
id | pubmed-8227788 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-82277882021-06-26 Bimodal Data Fusion of Simultaneous Measurements of EEG and fNIRS during Lower Limb Movements AL-Quraishi, Maged S. Elamvazuthi, Irraivan Tang, Tong Boon Al-Qurishi, Muhammad Adil, Syed Hasan Ebrahim, Mansoor Brain Sci Article Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have temporal and spatial characteristics that may complement each other and, therefore, pose an intriguing approach for brain-computer interaction (BCI). In this work, the relationship between the hemodynamic response and brain oscillation activity was investigated using the concurrent recording of fNIRS and EEG during ankle joint movements. Twenty subjects participated in this experiment. The EEG was recorded using 20 electrodes and hemodynamic responses were recorded using 32 optodes positioned over the motor cortex areas. The event-related desynchronization (ERD) feature was extracted from the EEG signal in the alpha band (8–11) Hz, and the concentration change of the oxy-hemoglobin (oxyHb) was evaluated from the hemodynamics response. During the motor execution of the ankle joint movements, a decrease in the alpha (8–11) Hz amplitude (desynchronization) was found to be correlated with an increase of the oxyHb (r = −0.64061, p < 0.00001) observed on the Cz electrode and the average of the fNIRS channels (ch28, ch25, ch32, ch35) close to the foot area representation. Then, the correlated channels in both modalities were used for ankle joint movement classification. The result demonstrates that the integrated modality based on the correlated channels provides a substantial enhancement in ankle joint classification accuracy of 93.01 ± 5.60% (p < 0.01) compared with single modality. These results highlight the potential of the bimodal fNIR–EEG approach for the development of future BCI for lower limb rehabilitation. MDPI 2021-05-27 /pmc/articles/PMC8227788/ /pubmed/34071982 http://dx.doi.org/10.3390/brainsci11060713 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article AL-Quraishi, Maged S. Elamvazuthi, Irraivan Tang, Tong Boon Al-Qurishi, Muhammad Adil, Syed Hasan Ebrahim, Mansoor Bimodal Data Fusion of Simultaneous Measurements of EEG and fNIRS during Lower Limb Movements |
title | Bimodal Data Fusion of Simultaneous Measurements of EEG and fNIRS during Lower Limb Movements |
title_full | Bimodal Data Fusion of Simultaneous Measurements of EEG and fNIRS during Lower Limb Movements |
title_fullStr | Bimodal Data Fusion of Simultaneous Measurements of EEG and fNIRS during Lower Limb Movements |
title_full_unstemmed | Bimodal Data Fusion of Simultaneous Measurements of EEG and fNIRS during Lower Limb Movements |
title_short | Bimodal Data Fusion of Simultaneous Measurements of EEG and fNIRS during Lower Limb Movements |
title_sort | bimodal data fusion of simultaneous measurements of eeg and fnirs during lower limb movements |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8227788/ https://www.ncbi.nlm.nih.gov/pubmed/34071982 http://dx.doi.org/10.3390/brainsci11060713 |
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