Low Latency Estimation of Motor Intentions to Assist Reaching Movements along Multiple Sessions in Chronic Stroke Patients: A Feasibility Study - Ibáñez, Jaime; Monge-Pereira, Esther; Molina-Rueda, Francisco; Serrano, J. I.; del Castillo, Maria D.; Cuesta-Gómez, Alicia; Carratalá-Tejada, María; Cano-de-la-Cuerda, Roberto; Alguacil-Diego, Isabel M.; Miangolarra-Page, Juan C.; Pons, Jose L. (Frontiers in Neuroscience, 2017)
Background: The association between motor-related cortical activity and peripheral stimulation with temporal precision has been proposed as a possible intervention to facilitate cortico-muscular pathways and thereby improve motor rehabilitation after stroke. Previous studies with patients have provided evidence of the possibility to implement brain-machine interface platforms able to decode motor intentions and use this information to trigger afferent stimulation and movement assistance. This study tests the use a low-latency movement intention detector to drive functional electrical stimulation assisting upper-limb reaching movements of patients with stroke. Methods: An eight-sessions intervention on the paretic arm was tested on four chronic stroke patients along one month. Patients' intentions to initiate reaching movements were decoded from electroencephalographic signals and used to trigger functional electrical stimulation that in turn assisted patients to do the task. The analysis of the patients’ ability to interact with the intervention platform, the assessment of changes in patients' clinical scales and of the system usability and the kinematic analysis of the reaching movements before and after the intervention period were carried to study the potential impact of the intervention. Results: On average 66.3 ± 15.7 % of trials (resting intervals followed by self-initiated movements) were correctly classified with the decoder of motor intentions. The average detection latency (with respect to the movement onsets estimated with gyroscopes) was 112 ± 278 ms. The Fügl-Meyer index upper extremity increased 11.5 ± 5.5 points with the intervention. The stroke impact scale also increased. In line with changes in clinical scales, kinematics of reaching movements showed a trend towards lower compensatory mechanisms. Patients’ assessment of the therapy reflected their acceptance of the proposed intervention protocol. Conclusions: According to results obtained here with a small sample of patients, Brain-Machine Interfaces providing low-latency support to upper-limb reaching movements in patients with stroke are a reliable and usable solution for motor rehabilitation interventions with potential functional benefits.