Brain-actuated functional electrical stimulation elicits lasting arm motor recovery after stroke

Brain-computer interfaces (BCI) are used in stroke rehabilitation to translate brain signals into intended movements of the paralyzed limb. However, the efficacy and mechanisms of BCI-based therapies remain unclear. Here we show that BCI coupled to functional electrical stimulation (FES) elicits significant, clinically relevant, and lasting motor recovery in chronic stroke survivors more effectively than sham FES. Such recovery is associated to quantitative signatures of functional neuroplasticity. BCI patients exhibit a significant functional recovery after the intervention, which remains 6–12 months after the end of therapy. Electroencephalography analysis pinpoints significant differences in favor of the BCI group, mainly consisting in an increase in functional connectivity between motor areas in the affected hemisphere. This increase is significantly correlated with functional improvement. Results illustrate how a BCI–FES therapy can drive significant functional recovery and purposeful plasticity thanks to contingent activation of body natural efferent and afferent pathways.

EEG Microstates for BCI Therapist Feedback: Preliminary Results on a Stroke Patient

Andrea Biasiucci, Ricardo Andres Chavarriaga Lozano, Robert Leeb, Hesam Sagha

Brain-Computer Interfaces convey a great potential in the field of stroke rehabilitation, where the continuous monitoring of the execution of mental tasks could support the positive effects of the therapy by reinforcing specific mental patterns. We propose the use of EEG Microstates as the building blocks of a novel BCI for Operators, and we show that preliminary results on a stroke patient seem to confirm that topographic information can provide hints on salient activity patterns on the affected hemisphere not recognizable within a simple discriminant framework. Furthermore, the technique could easily keep track of the evolution of these maps over different rehabilitation sessions, thus providing a strong hint of plasticity phenomena and cortical reorganization.

2011

Neurotechnology for Brain Repair

Andrea Biasiucci

Neurotechnology is the application of scientific knowledge to the practical purpose of understanding, interacting and/or repairing the brain or, in a broader sense, the nervous system. The development of novel approaches to decode functional information from the brain, to enhance specific properties of neural tissue and to restore motor output in real end-users is a fundamental challenge to translate these novel solutions into clinical practice. In this Thesis, I introduce i) a novel imaging method to characterize movement-related electroencephalographic (EEG) potentials; ii) a brain stimulation strategy to improve brain-computer interface (BCI) control; iii) and a therapy for motor recovery involving a neuroprosthesis. Overall, results show i) that stable EEG topographies present a subject-independent organization that can be used to robustly decode actual or attempted movements in sub-acute stroke patients and healthy controls, with minimal a-priori information; ii) that transcranial direct-current stimulation (tDCS) enhances the modulability of sensorimotor rhythms used for brain-computer interaction in chronic Spinal Cord Injured (SCI) individuals and healthy controls; iii) that neuromuscular electrical stimulation (NMES) controlled via closed-loop neural activity induces significantly stronger upper limb functional recovery in chronic stroke patients than sham NMES therapy, and that these changes are clinically relevant. These results have or might have important implications in i) disease diagnostics and monitoring through EEG; ii) assistive technology and reduction of permanent disability following SCI; iii) rehabilitation and recovery of upper limb function following a stroke, also after several years of complete paralysis. Briefly, this Thesis provides the conceptual framework, scientific rationale, technical details and clinical evidence supporting translational Neurotechnology that improves, optimizes and disrupts current medical practice in monitoring, substituting and recovering lost upper limb function.

EPFL2014

Motor Recovery After Stroke by Means of BCI-Guided Functional Electrical Stimulation

Andrea Biasiucci, Robert Leeb

Brain-Computer Interfaces (BCIs) provide a mean to access the damaged motor network of the brain after stroke, and could be used to drive and promote beneficial plasticity. Among the available therapeutic approaches, Functional Electrical Stimulation (FES) is often applied during rehabilitation to directly engage muscles of the affected side of the body, especially when the residual functionality is weak or absent. In this paper, we describe a BCI system for stroke rehabilitation that decodes the attempt to execute a sustained hand extension movement from non-invasive human EEG and activates FES of affected arm muscles, accordingly. The system allows the physical therapist to monitor current brain activity through an EEG-guided visualization. Preliminary results on 4 chronic stroke patients show consistency in the EEG features selected for further training. Three of the patients completed the testing, and they all show recovery of target muscle function. Our results support the idea that BCI can be used to promote beneficial plasticity even during chronic phase, and justify further testing on a larger population.

2013

Neurotechnology for Brain Repair

Andrea Biasiucci

EPFL2014