Motor imagery (MI) and action observation (AO) are mental practices commonly applied in brain-computer interface (BCI) systems for stroke rehabilitation. However, previous studies have reported that combined AO and MI (AOMI) is more effective than MI or AO alone in terms of enhanced eventrelated desynchronization (ERD), which expresses cortical excitability and improves the classification performance of the BCI system in healthy subjects. Nonetheless, evidence the use of this strategy in stroke patients is still lacking. Hence, this study aimed to investigate the effect of AOMI on classification performance and ERD in chronic stroke patients. Ten chronic stroke participants were recruited for this study. Each participant was asked to perform both MI (control condition) and AOMI (experimental condition) tasks. For the MI task, the participants requested to perform MI while gazing at a static arrow picture. For the AOMI task, the participants were given a video-guided movement while executing MI. An array of 16 Ag/AgCl electrodes were used to record electroencephalographic (EEG) data during the mental tasks to analyze ERD amplitudes. Common spatial patterns (CSPs) combined with support vector machines (SVMs) were employed to evaluate the classification performance (offline analysis) of the baseline and imagery classes under each condition. Our results indicated that the ERD values and classification accuracy in AOMI were significantly greater than those under MI conditions. Moreover, a significant negative correlation between ERD values and classification performance was also found. In other words, enhanced ERD values (more negative values) also increased classification performance.
Introduction: Upper extremity impairment is a problem usually found in poststroke patients, and it is seldom completely improved even following conventional physical therapy. Motor imagery (MI) and action observation (AO) therapy are mental practices that may regain motor function in poststroke patients, especially when integrating them with brain-computer interface (BCI) technology. However, previous studies have always investigated the effects of an MI- or AO-based BCI for stroke rehabilitation separately. Therefore, in this study, we aimed to propose the effectiveness of a combined AO and MI (AOMI)-based BCI with functional electrical stimulation (FES) feedback to improve upper limb functions and alter brain activity patterns in chronic stroke patients.Case presentation: A 53-year-old male who was 12 years post stroke was left hemiparesis and unable to produce any wrist and finger extension.Intervention: The participant was given an AOMI-based BCI with FES feedback 3 sessions per week for 4 consecutive weeks, and he did not receive any conventional physical therapy during the intervention. The Fugl-Meyer Assessment of Upper Extremity (FMA-UE) and active range of motion (AROM) of wrist extension were used as clinical assessments, and the laterality coefficient (LC) value was applied to explore the altered brain activity patterns affected by the intervention.Outcomes: The FMA-UE score improved from 34 to 46 points, and the AROM of wrist extension was increased from 0 degrees to 20 degrees. LC values in the alpha band tended to be positive whereas LC values in the beta band seemed to be slightly negative after the intervention.Conclusion: An AOMI-based BCI with FES feedback training may be a promising strategy that could improve motor function in poststroke patients; however, its efficacy should be studied in a larger population and compared to that of other therapeutic methods.Trial registration: Thai Clinical Trial Registry: TCTR20200821002. Registered 17 August 2020, http://www.thaiclinicaltrials.org
the study aimed to compare the effects of combined action observation and motor imagery (AOMI) and motor imagery (MI)-based brain-computer interface (BCI) training on upper limb recovery, cortical excitation, and cognitive task performance in chronic stroke patients. 17 chronic stroke patients were recruited and randomly assigned to AOMI-based BCI (n = 9) and MI-based BCI groups (n = 8). The AOMIbased BCI group received AOMI-based BCI training via functional electrical stimulation (FES) feedback, whereas the MI-based BCI group obtained MI-based BCI training via FES feedback. Both groups participated in training for 12 sessions (3 days/week, consecutive four weeks). To evaluate upper limb function recovery, the Fugl-Meyer Assessment for upper extremity (FMA-UE) was employed. Event-related desynchronization (ERD) and online classification accuracy were utilized to measure cortical excitation of the affected sensorimotor hand region and cognitive task performance, respectively. Both AOMI and MI-based BCI training improved upper limb function in chronic stroke patients. However, the AOMI-based BCI group showed significantly greater motor gain than the MI-based BCI group. In addition, the AOMI-based BCI group demonstrated significantly greater cortical excitation of the affected sensorimotor hand region and cognitive task performance. The correlation analysis revealed that higher cognitive task performance during AOMI-based BCI training may promote greater cortical excitation of the affected sensorimotor hand region, which contributes to greater upper limb function improvement compared to MI-based BCI training.
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