Brain–Computer Interface With Functional Electrical Stimulation Training for Upper-Extremity Rehabilitation Performance Outcomes

PURPOSE: The primary aim of this study is to examine rehabilitation outcomes in upper-extremity (UE) movement following a combined brain–computer interface (BCI) and functional electrical stimulation (FES) intervention. Overall, there is a gap in research regarding BCI–FES technology as a rehabilitation tool to enhance motor improvements in adults post stroke. While previous research has assessed motor improvements and underlying neural reorganization, rehabilitative effects of the treatment have not yet been examined. This research addresses the issue that many stroke survivors experience lingering hemiparesis, even after receiving traditional therapies. Additionally, this novel treatment holds promise for chronic stroke recovery, a time period often overlooked for continued therapy services.

DESIGN: A quasi-experimental, one-way repeated-measures design over time included 14 stroke survivors with four assessment points (pretreatment, during treatment, posttreatment, and 4-wk follow-up). Participants were included in the study if they were over age 18 yr with first-ever ischemic or hemorrhagic stroke resulting in residual UE deficits. Exclusion criteria included comorbid neurodegenerative disorders; other neurological or psychiatric disorders; cognitive deficits that would disrupt the ability to provide informed consent; allergy to electrode gel, surgical tape, and metals; current treatment for infectious diseases or having apparent oral lesions or inflammation; and pregnancy or possibility of becoming pregnant during the study. Recruitment was done through referrals and flyers posted at local clinics and hospitals.

METHOD: Objective UE fine and gross motor skills were examined at each assessment point using the Action Research Arm Test and the Nine Hole Peg Test. Self-report measures, the Stroke Impact Scale and the Motor Activity Log, measured participant satisfaction and perception of UE improvements at each assessment point. Friedman’s nonparametric tests were run for all four measures to assess any significant change over time.

RESULTS: After analysis, significant results were found for the following self-report outcomes: UE quality of use, amount of use, activities of daily living and instrumental activities of daily living, strength, hand function, recovery, memory and thinking, social participation, and overall recovery. Objective outcomes such as grip, grasp, pinch, gross motor, and hand dexterity skills did not significantly improve.

CONCLUSION: Significant improvements in self-reported outcomes showed that the BCI–FES intervention had a significant impact on participants’ daily functioning but did not produce significant outcomes with objective measures. This could mean several things. The objective measures may not have enough ecological validity to detect meaningful change. Also, the split sample (mild or severe stroke) may have impacted the results. Overall, a combined use of objective and subjective measures provides a more holistic assessment of functional gains following this intervention. The importance of our findings to future occupational therapy practice is twofold. First, BCI–FES may be an effective intervention for improved UE function in adults with hemiparesis, and second, the combined use of objective and subjective measures provides the clinician a more holistic view of clients’ progress and provides a way for clients to be more involved in their goal-setting and rehabilitation process.

References

Young, B. M., Nigogosyan, Z., Remsik, A., Walton, L. M., Song, J., Nair, V. A., . . . Prabhakaran, V. (2014). Changes in functional connectivity correlate with behavioral gains in stroke patients after therapy using a brain–computer interface device. Frontiers in Neuroengineering, 7, 25. http://doi.org/10.3389/fneng.2014.00025

Young, B. M., Nigogosyan, Z., Walton, L. M., Remsik, A., Song, J., Nair, V. A., . . . Prabhakaran, V. (2015). Dose–response relationships using brain–computer interface technology impact stroke rehabilitation. Frontiers in Human Neuroscience, 9, 361. http://doi.org/10.3389/fnhum.2015.00361

Young, B. M., Nigogosyan, Z., Walton, L. M., Song, J., Nair, V. A., Grogan, S. W., . . . Prabhakaran, V. (2014). Changes in functional brain organization and behavioral correlations after rehabilitative therapy using a brain–computer interface. Frontiers in Neuroengineering, 7, 26. http://doi.org/10.3389/fneng.2014.00026