학술논문
EEG Biomarkers Related With the Functional State of Stroke Patients.
Document Type
Academic Journal
Author
Sebastián-Romagosa M; Department of Physiology, Universitat Autònoma de Barcelona, Barcelona, Spain.; g.tec Medical Engineering Spain SL, Barcelona, Spain.; Udina E; Department of Physiology, Universitat Autònoma de Barcelona, Barcelona, Spain.; Ortner R; g.tec Medical Engineering Spain SL, Barcelona, Spain.; Dinarès-Ferran J; g.tec Medical Engineering Spain SL, Barcelona, Spain.; Data and Signal Processing Research Group, Department of Engineering, University of Vic - Central University of Catalonia, Vic, Spain.; Cho W; g.tec Medical Engineering GmbH, Schiedlberg, Austria.; Murovec N; g.tec Medical Engineering GmbH, Schiedlberg, Austria.; Matencio-Peralba C; g.tec Medical Engineering Spain SL, Barcelona, Spain.; Sieghartsleitner S; g.tec Medical Engineering GmbH, Schiedlberg, Austria.; Allison BZ; Department of Cognitive Science, University of California at San Diego, La Jolla, CA, United States.; Guger C; g.tec Medical Engineering Spain SL, Barcelona, Spain.; g.tec Medical Engineering GmbH, Schiedlberg, Austria.
Source
Publisher: Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101478481 Publication Model: eCollection Cited Medium: Print ISSN: 1662-4548 (Print) Linking ISSN: 1662453X NLM ISO Abbreviation: Front Neurosci Subsets: PubMed not MEDLINE
Subject
Language
English
ISSN
1662-4548
Abstract
Introduction: Recent studies explored promising new quantitative methods to analyze electroencephalography (EEG) signals. This paper analyzes the correlation of two EEG parameters, Brain Symmetry Index (BSI) and Laterality Coefficient (LC), with established functional scales for the stroke assessment.
Methods: Thirty-two healthy subjects and thirty-six stroke patients with upper extremity hemiparesis were recruited for this study. The stroke patients where subdivided in three groups according to the stroke location: Cortical, Subcortical, and Cortical + Subcortical. The participants performed assessment visits to record the EEG in the resting state and perform functional tests using rehabilitation scales. Then, stroke patients performed 25 sessions using a motor-imagery based Brain Computer Interface system (BCI). BSI was calculated with the EEG data in resting state and LC was calculated with the Event-Related Synchronization maps.
Results: The results of this study demonstrated significant differences in the BSI between the healthy group and Subcortical group ( P = 0.001), and also between the healthy and Cortical+Subcortical group ( P = 0.019). No significant differences were found between the healthy group and the Cortical group ( P = 0.505). Furthermore, the BSI analysis in the healthy group based on gender showed statistical differences ( P = 0.027). In the stroke group, the correlation between the BSI and the functional state of the upper extremity assessed by Fugl-Meyer Assessment (FMA) was also significant, ρ = -0.430 and P = 0.046. The correlation between the BSI and the FMA-Lower extremity was not significant (ρ = -0.063, P = 0.852). Similarly, the LC calculated in the alpha band has significative correlation with FMA of upper extremity (ρ = -0.623 and P < 0.001) and FMA of lower extremity (ρ = -0.509 and P = 0.026). Other important significant correlations between LC and functional scales were observed. In addition, the patients showed an improvement in the FMA-upper extremity after the BCI therapy (ΔFMA = 1 median [IQR: 0-8], P = 0.002).
Conclusion: The quantitative EEG tools used here may help support our understanding of stroke and how the brain changes during rehabilitation therapy. These tools can help identify changes in EEG biomarkers and parameters during therapy that might lead to improved therapy methods and functional prognoses.
(Copyright © 2020 Sebastián-Romagosa, Udina, Ortner, Dinarès-Ferran, Cho, Murovec, Matencio-Peralba, Sieghartsleitner, Allison and Guger.)
Methods: Thirty-two healthy subjects and thirty-six stroke patients with upper extremity hemiparesis were recruited for this study. The stroke patients where subdivided in three groups according to the stroke location: Cortical, Subcortical, and Cortical + Subcortical. The participants performed assessment visits to record the EEG in the resting state and perform functional tests using rehabilitation scales. Then, stroke patients performed 25 sessions using a motor-imagery based Brain Computer Interface system (BCI). BSI was calculated with the EEG data in resting state and LC was calculated with the Event-Related Synchronization maps.
Results: The results of this study demonstrated significant differences in the BSI between the healthy group and Subcortical group ( P = 0.001), and also between the healthy and Cortical+Subcortical group ( P = 0.019). No significant differences were found between the healthy group and the Cortical group ( P = 0.505). Furthermore, the BSI analysis in the healthy group based on gender showed statistical differences ( P = 0.027). In the stroke group, the correlation between the BSI and the functional state of the upper extremity assessed by Fugl-Meyer Assessment (FMA) was also significant, ρ = -0.430 and P = 0.046. The correlation between the BSI and the FMA-Lower extremity was not significant (ρ = -0.063, P = 0.852). Similarly, the LC calculated in the alpha band has significative correlation with FMA of upper extremity (ρ = -0.623 and P < 0.001) and FMA of lower extremity (ρ = -0.509 and P = 0.026). Other important significant correlations between LC and functional scales were observed. In addition, the patients showed an improvement in the FMA-upper extremity after the BCI therapy (ΔFMA = 1 median [IQR: 0-8], P = 0.002).
Conclusion: The quantitative EEG tools used here may help support our understanding of stroke and how the brain changes during rehabilitation therapy. These tools can help identify changes in EEG biomarkers and parameters during therapy that might lead to improved therapy methods and functional prognoses.
(Copyright © 2020 Sebastián-Romagosa, Udina, Ortner, Dinarès-Ferran, Cho, Murovec, Matencio-Peralba, Sieghartsleitner, Allison and Guger.)