Brain-Computer Interfaces With Multi-Sensory Feedback for Stroke Rehabilitation: A Case Study

2017 ◽  
Vol 41 (11) ◽  
pp. E178-E184 ◽  
Author(s):  
Danut C. Irimia ◽  
Woosang Cho ◽  
Rupert Ortner ◽  
Brendan Z. Allison ◽  
Bogdan E. Ignat ◽  
...  
Keyword(s):  
Stroke Rehabilitation ◽  
Sensory Feedback ◽  
Brain Computer Interfaces ◽  
Computer Interfaces

scholarly journals Investigating the impact of feedback update interval on the efficacy of restorative brain–computer interfaces

2017 ◽  
Vol 4 (8) ◽  
pp. 170660 ◽  
Author(s):  
Sam Darvishi ◽  
Michael C. Ridding ◽  
Brenton Hordacre ◽  
Derek Abbott ◽  
Mathias Baumert
Keyword(s):  
Sensory Feedback ◽  
Motor Evoked Potentials ◽  
Single Case ◽  
Maximum Voluntary Contraction ◽  
Voluntary Contraction ◽  
Brain Computer Interfaces ◽  
Computer Interfaces ◽  
Timely Fashion ◽  
Clinically Significant ◽  
The Impact

Restorative brain–computer interfaces (BCIs) have been proposed to enhance stroke rehabilitation. Restorative BCIs are able to close the sensorimotor loop by rewarding motor imagery (MI) with sensory feedback. Despite the promising results from early studies, reaching clinically significant outcomes in a timely fashion is yet to be achieved. This lack of efficacy may be due to suboptimal feedback provision. To the best of our knowledge, the optimal feedback update interval (FUI) during MI remains unexplored. There is evidence that sensory feedback disinhibits the motor cortex. Thus, in this study, we explore how shorter than usual FUIs affect behavioural and neurophysiological measures following BCI training for stroke patients using a single-case proof-of-principle study design. The action research arm test was used as the primary behavioural measure and showed a clinically significant increase (36%) over the course of training. The neurophysiological measures including motor evoked potentials and maximum voluntary contraction showed distinctive changes in early and late phases of BCI training. Thus, this preliminary study may pave the way for running larger studies to further investigate the effect of FUI magnitude on the efficacy of restorative BCIs. It may also elucidate the role of early and late phases of motor learning along the course of BCI training.

Brain-computer interfaces for stroke rehabilitation: summary of the 2016 BCI Meeting in Asilomar

2018 ◽  
Vol 5 (2-3) ◽  
pp. 41-57
Author(s):  
Christoph Guger ◽  
José del R. Millán ◽  
Donatella Mattia ◽  
Junichi Ushiba ◽  
Surjo R. Soekadar ◽  
...  
Keyword(s):  
Stroke Rehabilitation ◽  
Brain Computer Interfaces ◽  
Computer Interfaces

scholarly journals Self-Paced Online vs. Cue-Based Offline Brain–Computer Interfaces for Inducing Neural Plasticity

2019 ◽  
Vol 9 (6) ◽  
pp. 127 ◽  
Author(s):  
Mads Jochumsen ◽  
Muhammad Samran Navid ◽  
Rasmus Wiberg Nedergaard ◽  
Nada Signal ◽  
Usman Rashid ◽  
...  
Keyword(s):  
Electrical Stimulation ◽  
Neural Plasticity ◽  
Stroke Rehabilitation ◽  
Cortical Plasticity ◽  
Cortical Excitability ◽  
Motor Evoked Potentials ◽  
Brain Computer Interfaces ◽  
Post Intervention ◽  
Computer Interfaces ◽  
The Absolute

Brain–computer interfaces (BCIs), operated in a cue-based (offline) or self-paced (online) mode, can be used for inducing cortical plasticity for stroke rehabilitation by the pairing of movement-related brain activity with peripheral electrical stimulation. The aim of this study was to compare the difference in cortical plasticity induced by the two BCI modes. Fifteen healthy participants participated in two experimental sessions: cue-based BCI and self-paced BCI. In both sessions, imagined dorsiflexions were extracted from continuous electroencephalogram (EEG) and paired 50 times with the electrical stimulation of the common peroneal nerve. Before, immediately after, and 30 min after each intervention, the cortical excitability was measured through the motor-evoked potentials (MEPs) of tibialis anterior elicited through transcranial magnetic stimulation. Linear mixed regression models showed that the MEP amplitudes increased significantly (p < 0.05) from pre- to post- and 30-min post-intervention in terms of both the absolute and relative units, regardless of the intervention type. Compared to pre-interventions, the absolute MEP size increased by 79% in post- and 68% in 30-min post-intervention in the self-paced mode (with a true positive rate of ~75%), and by 37% in post- and 55% in 30-min post-intervention in the cue-based mode. The two modes were significantly different (p = 0.03) at post-intervention (relative units) but were similar at both post timepoints (absolute units). These findings suggest that immediate changes in cortical excitability may have implications for stroke rehabilitation, where it could be used as a priming protocol in conjunction with another intervention; however, the findings need to be validated in studies involving stroke patients.

P29 Neural correlates of post-stroke rehabilitation based on brain-computer interfaces: Preliminary outlook

2020 ◽  
Vol 131 (4) ◽  
pp. e192-e193
Author(s):  
K.A. Grigoryan ◽  
V. Nikulin ◽  
A. Anwander ◽  
K. Pine ◽  
N. Weiskopf ◽  
...  
Keyword(s):  
Stroke Rehabilitation ◽  
Neural Correlates ◽  
Brain Computer Interfaces ◽  
Post Stroke ◽  
Computer Interfaces

scholarly journals User-centered design in brain–computer interfaces—A case study

2013 ◽  
Vol 59 (2) ◽  
pp. 71-80 ◽  
Author(s):  
Martijn Schreuder ◽  
Angela Riccio ◽  
Monica Risetti ◽  
Sven Dähne ◽  
Andrew Ramsay ◽  
...  
Keyword(s):  
Brain Computer Interfaces ◽  
User Centered Design ◽  
Computer Interfaces ◽  
User Centered
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