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Improving Real-Time Lower Limb Motor Imagery Detection Using tDCS and an Exoskeleton
Marisol Rodríguez-Ugarte1, Eduardo Iáñez1, Mario Ortiz1
1Brain-Machine Interface Systems Lab, Systems Engineering and Automation Department, Miguel Hernández University of Elche, Elche, Spain.
Frontiers in Neuroscience
|November 9, 2018
Summary
A novel transcranial direct current stimulation (tDCS) method improved motor imagery (MI) detection accuracy using brain-machine interfaces (BMI). Active tDCS significantly boosted accuracy compared to sham stimulation, suggesting potential for neurorehabilitation.
Area of Science:
- Neuroscience
- Rehabilitation Engineering
- Brain-Computer Interfaces
Background:
- Motor imagery (MI) detection is crucial for neurorehabilitation.
- Brain-machine interfaces (BMIs) using electroencephalography (EEG) show promise for decoding motor intentions.
- Transcranial direct current stimulation (tDCS) can modulate cortical excitability.
Purpose of the Study:
- To evaluate a novel tDCS montage for enhancing lower limb motor imagery detection accuracy.
- To assess the efficacy of a real-time EEG-based BMI for distinguishing between relax and gait MI states.
- To compare the impact of visual versus exoskeleton feedback on MI detection accuracy.
Main Methods:
- A custom tDCS montage with two anodes (right cerebrocerebellum, Cz) and one cathode (FC2) was applied.
- An EEG-based BMI was developed to detect MI states based on power spectrum differences.
- Two single-blind experiments (E1: visual feedback, E2: exoskeleton feedback) were conducted with sham and active tDCS groups.
Main Results:
- Active tDCS improved MI detection accuracy by 12.6% (E1) and 8.2% (E2) compared to sham.
- Mean detection accuracies were 65% (E1) and 81.6% (E2) for active tDCS groups.
- Exoskeleton feedback (E2) enhanced accuracy by 16.7% (active tDCS) and 21.2% (sham) over visual feedback (E1).
Conclusions:
- The novel tDCS montage effectively enhances motor imagery detection accuracy.
- Real-time exoskeleton feedback shows potential for improving MI-based BMI performance.
- Further research with larger cohorts is warranted to confirm the efficacy for cerebrovascular accident (CVA) patient rehabilitation.
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