Abstract
Stroke is a leading cause of motor disability worldwide. Upper limb rehabilitation is particularly challenging since approximately 35% of patients recover significant hand function after 6 months of the stroke's onset. Therefore, new therapies, especially those based on brain-computer interfaces (BCI) and robotic assistive devices, are currently under research. Electroencephalography (EEG) acquired brain rhythms in alpha and beta bands, during motor tasks, such as motor imagery/intention (MI), could provide insight of motor-related neural plasticity occurring during a BCI intervention. Hence, a longitudinal analysis of subacute stroke patients' brain rhythms during a BCI coupled to robotic device intervention was performed in this study. Data of 9 stroke patients were acquired across 12 sessions of the BCI intervention. Alpha and beta event-related desynchronization/synchronization (ERD/ERS) trends across sessions and their association with time since stroke onset and clinical upper extremity recovery were analyzed, using correlation and linear stepwise regression, respectively. More EEG channels presented significant ERD/ERS trends across sessions related with time since stroke onset, in beta, compared to alpha. Linear models implied a moderate relationship between alpha rhythms in frontal, temporal, and parietal areas with upper limb motor recovery and suggested a strong association between beta activity in frontal, central, and parietal regions with upper limb motor recovery. Higher association of beta with both time since stroke onset and upper limb motor recovery could be explained by beta relation with closed-loop communication between the sensorimotor cortex and the paralyzed upper limb, and alpha being probably more associated with motor learning mechanisms. The association between upper limb motor recovery and beta activations reinforces the hypothesis that broader regions of the cortex activate during movement tasks as a compensatory mechanism in stroke patients with severe motor impairment. Therefore, EEG across BCI interventions could provide valuable information for prognosis and BCI cortical activity targets.
Highlights
Stroke is one of the leading causes of disability worldwide [1]
Studies have described that stroke patients can still elicit event-related desynchronization or synchronization (ERD/ERS) during motor imagery/intention (MI) of their paralyzed hand [10, 11] and during passive movement provided by robotic assistive devices [12]
Other areas such as frontal, temporal, and parietal regions showed significant changes across sessions in alpha and/or beta and in some patients these changes presented a significant association with time since stroke. This implied that regions usually not associated with motor tasks could be recruited in stroke patients during MI of their impaired upper limb. This is reinforced by the observed evolution of compared activity in frontal affected hemisphere (AH) and central unaffected hemisphere (UH) across sessions, since similar activations were more likely to be observed over these regions in alpha and beta in earlier sessions and afterwards changed towards more pronounced activations in frontal AH compared to central UH, in later sessions of the intervention
Summary
Stroke is one of the leading causes of disability worldwide [1]. Ischemic stroke is the most common type and has a global incidence of approximately 11.6 million new cases per year [1]. Therapies based on robot assistive devices have shown potential for increasing stroke patients’ neuroplasticity, the main recovery mechanism of stroke [2]. Some of these devices are designed for upper limb motor rehabilitation by applying passive movement to stroke patients’ paralyzed hand [3,4,5,6]. Since ERD/ERS is associated with increased or decreased brain activity, it has been hypothesized that BCI systems controlled by hand MI and coupled to robotic assistive devices could be used to promote stroke patients’ neuroplasticity processes, increasing the probability of upper limb function recovery [13, 14]
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have