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Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients
Published on: April 18, 2025
Hybrid Brain-Computer Interface for Controlling a Wearable Lower-Limb Exoskeleton with Augmented Reality Glasses for
Abstract:
Conventional crutch-based control for lowerlimb exoskeletons often imposes a considerable physical burden and limits usability. To address these challenges, we developed a hybrid brain-computer interface (BCI) combining a steady-state visual evoked potential (SSVEP)- based BCI with asynchronous biosignal-based switches triggered by a wink and teeth clench. Practical usability was improved by implementing a wearable headband-type biosignal-recording device to acquire electroencephalography, electromyography, and electrooculography signals. Augmented reality glasses were used to present visual stimuli and gait guidance information. To support robust exoskeleton control in a wearable BCI environment, we proposed an asynchronous operational framework in which SSVEP responses were used for movement-mode selection, whereas wink- and clench-based switches were assigned to command execution and cancellation, respectively. Ten participants completed real-time walking experiments while wearing a custom lower-limb exoskeleton using both the conventional crutch-based and proposed control methods. The performance of the proposed system was evaluated using BCI classification accuracy and F1-scores for two asynchronous switches, whereas usability and workload were assessed using the system usability scale (SUS) and NASA task load index (NASA-TLX), respectively. Despite gross body movement during exoskeleton-assisted walking, the proposed hybrid control framework demonstrated robust mode selection, execution, and cancellation with an average SSVEP classification accuracy of 95.06%, F1-scores of 99.80% and 99.22% for the wink- and clench-based switches, respectively. Notably, only two false positive events were observed per switch across all participants. Furthermore, the proposed method exhibited a significantly higher SUS score than the crutch-based control method (78.25 vs. 53.50; p < 0.01) and a significantly lower physical demand in the NASATLX (3.15 vs. 7.85; p < 0.05), confirming its potential as a practical alternative. To the best of our knowledge, this is among the first studies in which a wearable hybrid SSVEPbased BCI for lower-limb exoskeleton operation applicable to real-world walking tasks was systematically demonstrated. Our findings suggest that the proposed hybrid BCI is a robust and less physically demanding alternative to a conventional control method, offering strong potential for daily assistance and gait rehabilitation.

