BCI for stroke rehabilitation: motor and beyond

R Mane, T Chouhan, C Guan - Journal of neural engineering, 2020 - iopscience.iop.org
Stroke is one of the leading causes of long-term disability among adults and contributes to
major socio-economic burden globally. Stroke frequently results in multifaceted impairments …

[HTML][HTML] State-of-the-art non-invasive brain–computer interface for neural rehabilitation: A review

M Zhuang, Q Wu, F Wan, Y Hu - Journal of Neurorestoratology, 2020 - Elsevier
Brain–computer interface (BCI) is a novel communication method between brain and
machine. It enables signals from the human brain to influence or control external devices …

EEG-based cognitive control behaviour assessment: an ecological study with professional air traffic controllers

G Borghini, P Aricò, G Di Flumeri, G Cartocci… - Scientific reports, 2017 - nature.com
Several models defining different types of cognitive human behaviour are available. For this
work, we have selected the Skill, Rule and Knowledge (SRK) model proposed by …

Brain‐computer interface for clinical purposes: Cognitive assessment and rehabilitation

L Carelli, F Solca, A Faini, P Meriggi… - BioMed research …, 2017 - Wiley Online Library
Alongside the best‐known applications of brain‐computer interface (BCI) technology for
restoring communication abilities and controlling external devices, we present the state of …

Neurofeedback as a form of cognitive rehabilitation therapy following stroke: A systematic review

T Renton, A Tibbles, J Topolovec-Vranic - PloS one, 2017 - journals.plos.org
Neurofeedback therapy (NFT) has been used within a number of populations however it has
not been applied or thoroughly examined as a form of cognitive rehabilitation within a stroke …

A network neuroscience of human learning: potential to inform quantitative theories of brain and behavior

DS Bassett, MG Mattar - Trends in cognitive sciences, 2017 - cell.com
Humans adapt their behavior to their external environment in a process often facilitated by
learning. Efforts to describe learning empirically can be complemented by quantitative …

The time-varying networks in P300: a task-evoked EEG study

F Li, B Chen, H Li, T Zhang, F Wang… - … on Neural Systems …, 2016 - ieeexplore.ieee.org
P300 is an important event-related potential that can be elicited by external visual, auditory,
and somatosensory stimuli. Various cognition-related brain functions (ie, attention …

Effects of motor imagery based brain-computer interface on upper limb function and attention in stroke patients with hemiplegia: a randomized controlled trial

X Liu, W Zhang, W Li, S Zhang, P Lv, Y Yin - BMC neurology, 2023 - Springer
Background Seeking positive and comprehensive rehabilitation methods after stroke is an
urgent problem to be solved, which is very important to improve the dysfunction of stroke …

Toward an adapted neurofeedback for post-stroke motor rehabilitation: state of the art and perspectives

S Le Franc, G Herrera Altamira, M Guillen… - Frontiers in Human …, 2022 - frontiersin.org
Stroke is a severe health issue, and motor recovery after stroke remains an important
challenge in the rehabilitation field. Neurofeedback (NFB), as part of a brain–computer …

Emerging frontiers of neuroengineering: a network science of brain connectivity

DS Bassett, AN Khambhati… - Annual review of …, 2017 - annualreviews.org
Neuroengineering is faced with unique challenges in repairing or replacing complex neural
systems that are composed of many interacting parts. These interactions form intricate …