Objective. Combining repetitive transcranial magnetic stimulation (rTMS) with brain-computer interface (BCI) training can address motor impairment after stroke by down-regulating exaggerated inhibition from the contralesional hemisphere and encouraging ipsilesional activation. The objective was to evaluate the efficacy of combined rTMS+BCI, compared to sham rTMS+BCI, on motor recovery after stroke in subjects with lasting motor paresis. Approach. Three stroke subjects approximately one year post-stroke participated in three weeks of combined rTMS (real or sham) and BCI, followed by three weeks of BCI alone. Behavioral and electrophysiological differences were evaluated at baseline, after three weeks, and after six weeks of treatment. Main Results. Motor improvements were observed in both real rTMS+BCI and sham groups, but only the former showed significant alterations in inter-hemispheric inhibition in the desired direction and increased relative ipsilesional cortical activation from fMRI. In addition, significant improvements in BCI performance over time and adequate control of the virtual reality BCI paradigm were observed only in the former group. Significance. When combined, the results highlight the feasibility and efficacy of combined rTMS+BCI for motor recovery, demonstrated by increased ipsilesional motor activity and improvements in behavioral function for the real rTMS+BCI condition in particular. Our findings also demonstrate the utility of BCI training alone, as demonstrated by behavioral improvements for the sham rTMS+BCI condition. This study is the first to evaluate combined rTMS and BCI training for motor rehabilitation and provides a foundation for continued work to evaluate the potential of both rTMS and virtual reality BCI training for motor recovery after stroke.
According to the World Health Organization (WHO), neurological disorders and injuries account for the 6.3% of the global burden of disease (GBD) (1, 2). With more than 6% of DALY (disability-adjusted life years) in the world, neurological disorders represent one of the most widespread clinical condition. Among neurological disorders, more than half of the burden in DALYs is constituted by cerebral-vascular disease (55%), such as stroke. Stroke, together with spinal cord injury (SCI), accounts for 52% of the adult-onset disability and, over a billion people (i.e., about a 15% of the population worldwide) suffer from some form of disability (3). These numbers are likely to increase in the coming years due to the aging of the population (4), since disorders affecting people aged 60 years and older contribute to 23% of the total GBD (5).
Standard physical rehabilitation favors the functional recovery after stroke, as compared to no treatment (6). However, the functional recovery is not always satisfactory as only 20% of patients fully resume their social life and job activities (7). Hence, the need of more effective and patient-tailored rehabilitative approaches to maximize the functional outcome of neurological injuries as well as patients’ quality of life (8). Modern technological methodologies represent one of the most recent advances in neurorehabilitation, and an increasing body of evidence supports their role in the recovery from brain and/or medullary insults. This manuscript provides a perspective on how technologies and methodologies could be combined in order to maximize the outcome of neurorehabilitation.
Current Systems and Therapeutic Approaches for Neurorehabilitation
The great progress made in interdisciplinary fields, such as neural engineering (9, 10), has allowed to investigate many neural mechanisms, by detecting and processing the neural signals at high spatio-temporal resolution, and by interfacing the nervous system with external devices, thus restoring neurological functions lost due to disease/injury. The progress continues in parallel to technological advancements. The last two decades there has seen a large proliferation of technological approaches for human rehabilitation, such as robots, wearable systems, brain stimulation, and virtual environments. In the next sections, we will focus on: robotic therapy, non-invasive brain stimulation (NIBS), and neural interfaces.
Robots for neurorehabilitation are designed to support the administration of physical exercises to the upper or lower extremities, with the purpose of promoting neuro-motor recovery. This technology has a relatively long history, dating back to the early 1990s (11). Robot devices for rehabilitation differ widely in terms of mechanical design, number of degrees of freedom, and control architectures. As regards the mechanical design, robots may have either a single point of interaction (i.e., end effector) with the user body (endpoint robots or manipulanda) or multiple points of interaction (exoskeletons and wearable robots) (12).
Endpoint robots for the upper extremity, include Inmotion2 (IMT, USA) (13), KINARM End-Point (BKIN, Canada), and Braccio di Ferro (14) (Figure 1A1, left). Only some of these devices have been tested in randomized clinical trials (15), confirming an improvement of upper limb motor function after stroke (16). However, convincing evidence in favor of significant changes in activities of daily living (ADL) indicators is lacking (17), possibly because performance in ADL is highly affected by hand functionality. A good example of lower limb endpoint robot is represented by gait trainer GT1 (Reha-Stim, Germany). Its efficacy was tested by Picelli et al. (18), who demonstrated an improvement in multiple clinical measures in subjects with Parkinson’s disease following robotic-assisted rehabilitation when compared to physical rehabilitation alone (18). Endpoint robots are also available for postural rehabilitation. For instance, Hunova (Movendo Technology, Italy, launched in 2017) is equipped with a seat and a platform that induce multidirectional movements to improve postural stability (Figure 1A1, right).