EEG Biomarkers Related With the Functional State of Stroke Patients

Introduction: Recent studies show new methods to analyze electroencephalography (EEG) signals. This paper analyzes the correlation of two EEG parameters Brain Symmetry Index (BSI) and Laterality Coefficient (LC) with the most extended 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 resting state and functionals test 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 have been 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, rho = -0.430 and P = 0.046. The correlation between the BSI and the FMA-Lower extremity was not significant (rho = -0.063, P = 0.852). Similarily, the LC calculated in the alpha band has significative correlation with FMA of upper extremity (rho = -0.623 and P < 0.001) and FMA of lower extremity (rho = -0.509 and P = 0.026). Other important significant correlations between LC and functional scales have been 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 EEG biomarkers analyzed in this study demonstrate that quantitative EEG tool is important for the stroke assessment and functional prognosis. These parameters could be a useful tool to detect brain changes.