BCI controlled neuromuscular electrical stimulation enables sustained motor recovery in chronic stroke victims

@inproceedings{Leeb2016BCICN,
  title={BCI controlled neuromuscular electrical stimulation enables sustained motor recovery in chronic stroke victims},
  author={Robert Leeb and Andrea Biasiucci and Thomas Schmidlin and Tiffany Corbet and Philippe Vuadens and Jos{\'e} del R. Mill{\'a}n},
  year={2016}
}
Introduction: Recently, it has been shown that brain-computer interfaces (BCI) can be used in stroke rehabilitation to decode motor attempts from brain signals and to trigger movements of the paralyzed limb [1]. Among other available practices in rehabilitation, neuromuscular electrical stimulation (NMES) is often used to directly engage muscles on the affected parts of the body during physical therapy. Nevertheless, the benefits of a combined approach, to directly link the brain intention with… 
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11 Citations
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Methods Citations
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11 Citations

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Citation Type

Brain-computer interfaces for stroke rehabilitation: summary of the 2016 BCI Meeting in Asilomar
TLDR
This work reviews work from eight groups that each presented recent results with BCI-based rehabilitation at a workshop during the 6th International Brain-Computer Interface Meeting and presents major directions and challenges for future research.
Efficacy and Brain Imaging Correlates of an Immersive Motor Imagery BCI-Driven VR System for Upper Limb Motor Rehabilitation: A Clinical Case Report
TLDR
Examining the efficacy of an EEG-based BCI-VR system using a MI paradigm for post-stroke upper limb rehabilitation on functional assessments, and related changes in MI ability and brain imaging found important improvements in upper extremity scores (Fugl-Meyer) and increases in brain activation measured by fMRI that suggest neuroplastic changes in brain motor networks.
Brain-Computer Interfaces for Post-Stroke Motor Rehabilitation: A Meta-Analysis
TLDR
A medium to large effect size of BCI therapy compared to controls suggests that BCI technology might be an effective intervention for post-stroke upper limb rehabilitation, however, more studies with larger sample size are required to increase the reliability of these results.
Longitudinal Electroencephalography Analysis in Subacute Stroke Patients During Intervention of Brain–Computer Interface With Exoskeleton Feedback
TLDR
Patients who presented increasingly stronger or continuously strong activations (ERD) may obtain better motor recovery and brain–computer interface performance can be an index to evaluate the efficacy of BCI intervention.
Changes in EEG Brain Connectivity Caused by Short-Term BCI Neurofeedback-Rehabilitation Training: A Case Study
TLDR
The MI-BCI training’s short-term effects does not show up in the ERD analysis significantly but can be detected by ERP-based network analysis significantly.
Brain‐computer interfaces for post‐stroke motor rehabilitation: a meta‐analysis
TLDR
Motor improvements, mostly quantified by the upper limb Fugl‐Meyer Assessment (FMA‐UE), exceeded the minimal clinically important difference in six BCI studies, while such improvement was reached only in three control groups, suggesting that BCI technology could be an effective intervention for post‐stroke upper limb rehabilitation.
Sensory threshold neuromuscular electrical stimulation fosters motor imagery performance
Development of a combined, sequential real-time fMRI and fNIRS neurofeedback system to enhance motor learning after stroke
Brain oscillatory activity as a biomarker of motor recovery in chronic stroke
TLDR
The results indicate that initial alpha desynchronization might be key for stratification of patients undergoing BMI interventions and that its interhemispheric balance plays an important role in motor recovery.
A Survey on the Use of Haptic Feedback for Brain-Computer Interfaces and Neurofeedback
TLDR
This survey reviews the various haptic technologies and describes their application to BCIs and NF, and identifies major trends in the use of haptic interfaces for BCI and NF systems and discusses crucial aspects that could motivate further studies.
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References

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Brain-machine interface in chronic stroke rehabilitation
  • Ann Neurol
  • 2013
DOI: 10.3217/978-3-85125-467-9-108 Proceedings of the 6th International Brain-Computer Interface Meeting, organized by the BCI Society Published by Verlag der TU Graz
  • DOI: 10.3217/978-3-85125-467-9-108 Proceedings of the 6th International Brain-Computer Interface Meeting, organized by the BCI Society Published by Verlag der TU Graz