Application of BCI systems in neurorehabilitation: a scoping review

Abstract

This review discussed various applications of BCI in rehabilitation and showed how BCI can be used to improve the quality of life for people with neurological disabilities. It will develop and promote new models of communication and finally, will create an accurate, reliable, online communication between human brain and computer and reduces the negative effects of external stimuli on BCI performance. Implications for Rehabilitation The field of brain-computer interfaces (BCI) is rapidly advancing and it is expected to fulfill a critical role in rehabilitation of neurological disorders and in movement restoration in the forthcoming years. In the near future, BCI has notable potential to become a major tool used by people with disabilities to control locomotion and communicate with surrounding environment and, consequently, improve the quality of life for many affected persons. Electrical field recording at the scalp (i.e. electroencephalography) is the most likely method to be of practical value for clinical use as it is simple and non-invasive. However, some aspects need future improvements, such as the ability to separate close imagery signal (motion of extremities and phalanges that are close together).

Designing an Interval Type-2 Fuzzy Logic System for Handling Uncertainty Effects in Brain–Computer Interface Classification of Motor Imagery Induced EEG Patterns

“…Thus, refinement of the algorithm was necessary. The original spMCA [39] was iterated several times (15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) with the core input data shuffled and appended with the data points representing means of clusters found in the previous iteration. For each iteration the record of a cluster validity index (described below) was kept.…”

“…The outcome of these investigations has intrinsic implications for the broader field of EEG-based brain-computer interface (BCI). The significance of BCI technology is reflected in its contribution to the improvement of living standards for people affected from neuromuscular disorders [12], [13] and, more recently, in its potential to support a range of rehabilitative therapies [14], [15] as well as the growing impact on computer games industry [16]. One of the key challenges in the field of EEGbased BCI is nondeterministic and nonstationary variability of the brain dynamics, reflected in EEG, which renders its interpretation particularly demanding [12], [17]- [19].…”

Brain Functional Networks Study of Subacute Stroke Patients With Upper Limb Dysfunction After Comprehensive Rehabilitation Including BCI Training

“…EEG-based BCI strategies have been recently proposed as a promising stroke neurorehabilitation strategy to treat symptoms, including paralysis, cognitive disorders, and aphasia (19)(20)(21)(22)(23)(24)(25). Despite the large heterogeneity in the available literature, there is consensus that BCI-based training can help to improve UL motor function in stroke patients.…”

Wink based facial expression classification using machine learning approach

“…Plenty of neurological diseases including brainstem stroke, spinal cord injury, multiple sclerosis, cerebral palsy, muscular dystrophies and amyotrophic lateral sclerosis (ALS) may impair the person's regular communication pathways [1]. If individuals are drastically affected by these neural disorders, they may partially or completely lose their voluntary muscle control.…”