Sep 2026· IEEE transactions on neural systems and rehabilitation engineering· Vol 34, pp. 3902-3912· 0 citations· 44 references
Medicine
TL;DR
This is among the first studies in which a wearable hybrid SSVEP-based BCI for lower-limb exoskeleton operation applicable to real-world walking tasks was systematically demonstrated and suggests that the proposed hybrid BCI is a robust and less physically demanding alternative to a conventional control method.
Abstract
Conventional crutch-based control for lower-limb 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 electroencephalogra-phy, 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; ${p} \lt 0.01$ ) and a significantly lower physical demand in the NASA-TLX (3.15 vs. 7.85; ${p} \lt 0.05$ ), confirming its potential as a practical alternative. To the best of our knowledge, this is among the first studies in which a wearable hybrid SSVEP-based 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.
Electroencephalography-based brain-computer interfaces (EEG-based BCIs) provide a non-invasive pathway for incorporating voluntary neural activity into lower-limb rehabilitation robots, exoskeletons, robotic orthoses, and gaittraining systems. This focused review examines the MI-based brain-robot rehabilitation loop, i...
Yong-Kang Li, Ai-Hui Wang, Xin-Yu Liu et al.· International Conference on...· 0 citations
CM-FuseNet is presented, an attention-augmented hybrid Brain–Computer–Muscle Interface that simultaneously fuses cortical concentration indices extracted from electroencephalography (EEG) and lower-limb intention patterns derived from electromyography (EMG) to adaptively control a 4-DOF assistive lower-limb exoskeleton...
Yongseong Park, D. Shin, Hun-kee Kim· Applied Sciences· 0 citations
Background: Recent advancements in enabling technologies, including artificial intelligence and telemedicine, alongside robust clinical study outcomes, have led to significant progress in upper limb and hand exoskeletons utilised for post-stroke rehabilitation. Objectives: This review aims to synthesize the recent scie...
Alberto Borboni, M. Verzeletti, Alireza Rastegarpanah et al.· Italian National Conference...· 0 citations
Background Wearable lower-limb exoskeletons have the potential to support intention-driven control of lower-limb exoskeletons, but existing control strategies often rely on mechanical or manual triggers that fail to capture user intent. Method Subjects were recruited from 23/9/2024 to 10/2/2025. A BiLSTM detector was p...
Ke Wang, Wen-Shan Li, Dan-Yang Ding et al.· Frontiers in Neurorobotics· 0 citations
Many wearable interface solutions use external computing systems—such as a computer—to infer actions from gestures, limiting feedback to a single vibrotactile or visual channel and rarely reporting on execution times or energy consumption. This paper presents the design and implementation of a wearable single-handed co...
Unax Arregi, N. Medrano, Belén Calvo· Applied Sciences· 0 citations
A first-in-human demonstration of the feasibility of device-embedded inertial sensing for gait-responsive DBS is provided and a practical framework for further evaluation in larger cohorts is established.
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