Brain–machine interfaces in neurorehabilitation of stroke

Abstract

Stroke is among the leading causes of long-term disabilities leaving an increasing number of people with cognitive, affective and motor impairments depending on assistance in their daily life. While function after stroke can significantly improve in the first weeks and months, further recovery is often slow or non-existent in the more severe cases encompassing 30-50% of all stroke victims. The neurobiological mechanisms underlying recovery in those patients are incompletely understood. However, recent studies demonstrated the brain's remarkable capacity for functional and structural plasticity and recovery even in severe chronic stroke. As all established rehabilitation strategies require some remaining motor function, there is currently no standardized and accepted treatment for patients with complete chronic muscle paralysis. The development of brain-machine interfaces (BMIs) that translate brain activity into control signals of computers or external devices provides two new strategies to overcome stroke-related motor paralysis. First, BMIs can establish continuous high-dimensional brain-control of robotic devices or functional electric stimulation (FES) to assist in daily life activities (assistive BMI). Second, BMIs could facilitate neuroplasticity, thus enhancing motor learning and motor recovery (rehabilitative BMI). Advances in sensor technology, development of non-invasive and implantable wireless BMI-systems and their combination with brain stimulation, along with evidence for BMI systems' clinical efficacy suggest that BMI-related strategies will play an increasing role in neurorehabilitation of stroke.

A review of the progression and future implications of brain-computer interface therapies for restoration of distal upper extremity motor function after stroke

“…Despite technological advancements in health care and increased preventative measures such as education and public emphasis on healthy living practices, the incidence of stroke is anticipated to rise annually, increasing by 20% as early as 2030 [1]. Demographic factors will likely contribute to this trend with an increasing elderly population in America [4]. However, stroke rates have declined significantly in persons 60 years and older, but largely persist in adults aged 45–59 years of age [2].…”

“…Potentially relying on the ability of residual motor neurons to fire and facilitate device control, BCIs help to train persisting cortical connections to execute motor output of the hand [4,7,8]. …”

Embodied neurofeedback with an anthropomorphic robotic hand

“…It is, however, only applicable in patients with residual motor skills. For fully plegic patients, alternative interventions are needed, such as mirror visual feedback (MVF)5 or neurofeedback-guided motor imagery training (NF-MIT)6. These interventions do not require residual motor function, as they address motor recovery through mere motor simulation.…”

Interfacing brain with computer to improve communication and rehabilitation after brain damage

“…This approach has been developed further to use the information on brain activity derived from the BCI to trigger the neuromodulation paradigm with the optimal timing and condition (Plow et al, 2009;Soekadar et al, 2014;Walter et al, 2012). This "brain-to-brain" approach, which has demonstrated outstanding potential when studied invasively in animals (Jackson et al, 2006), could be listed as a third strategy besides the previously mentioned "brain-to-function" and "brain-to-limb" approaches (see Fig.…”