ArticleSensors (Basel, Switzerland)2020
Developing a Motor Imagery-Based Real-Time Asynchronous Hybrid BCI Controller for a Lower-Limb Exoskeleton.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 88 citations in OpenAlex.
- Decoding Upper-Limb Motor Imagery from EEG Signals: A Systematic Review of Methods and Applications.Annals of biomedical engineering · 2026Pooled it
- Systematic review of AI/ML applications in multi-domain robotic rehabilitation: trends, gaps, and future directions.Journal of neuroengineering and rehabilitation · 2025Pooled it
- Motor imagery BCI enables more practical and user-friendly exoskeleton control than smartwatch for users with spinal cord injury: a preliminary study.Journal of neuroengineering and rehabilitation · 2026Article
- Improved performance of fNIRS-BCI by stacking of deep learning-derived frequency domain features.PloS one · 2025Article
- Decoding lower-limb kinematic parameters during pedaling tasks using deep learning approaches and EEG.Medical & biological engineering & computing · 2024Article
- MACNet: A Multidimensional Attention-Based Convolutional Neural Network for Lower-Limb Motor Imagery Classification.Sensors (Basel, Switzerland) · 2024Article
- Improving inter-session performance via relevant session-transfer for multi-session motor imagery classification.Heliyon · 2024Article
- Multiclass Classification of Visual Electroencephalogram Based on Channel Selection, Minimum Norm Estimation Algorithm, and Deep Network Architectures.Sensors (Basel, Switzerland) · 2024Article
- Brain-machine interface based on deep learning to control asynchronously a lower-limb robotic exoskeleton: a case-of-study.Journal of neuroengineering and rehabilitation · 2024Article
- Brain-computer interface enhanced by virtual reality training for controlling a lower limb exoskeleton.iScience · 2023Article
- A Comprehensive Review of Endogenous EEG-Based BCIs for Dynamic Device Control.Sensors (Basel, Switzerland) · 2022Review
- Identification of Lower-Limb Motor Tasks via Brain-Computer Interfaces: A Topical Overview.Sensors (Basel, Switzerland) · 2022Review
- Sensors and Actuation Technologies in Exoskeletons: A Review.Sensors (Basel, Switzerland) · 2022Review
- Decoding EEG rhythms offline and online during motor imagery for standing and sitting based on a brain-computer interface.Frontiers in neuroinformatics · 2022Article
- Involvement of the Rostromedial Prefrontal Cortex in Human-Robot Interaction: fNIRS Evidence From a Robot-Assisted Motor Task.Frontiers in neurorobotics · 2022Article
- High-Frequency Vibrating Stimuli Using the Low-Cost Coin-Type Motors for SSSEP-Based BCI.BioMed research international · 2022Article
- Electroencephalogram and surface electromyogram fusion-based precise detection of lower limb voluntary movement using convolution neural network-long short-term memory model.Frontiers in neuroscience · 2022Article
- Use of Force Feedback Device in a Hybrid Brain-Computer Interface Based on SSVEP, EOG and Eye Tracking for Sorting Items.Sensors (Basel, Switzerland) · 2021Article
- Multi-Domain Convolutional Neural Networks for Lower-Limb Motor Imagery Using Dry vs. Wet Electrodes.Sensors (Basel, Switzerland) · 2021Article
- Recognition of EEG Signals from Imagined Vowels Using Deep Learning Methods.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
This study aimed to develop an intuitive gait-related motor imagery (MI)-based hybrid brain-computer interface (BCI) controller for a lower-limb exoskeleton and investigate the feasibility of the controller under a practical scenario including stand-up, gait-forward, and sit-down. A filter bank common spatial pattern (FBCSP) and mutual information-based best individual feature (MIBIF) selection were used in the study to decode MI electroencephalogram (EEG) signals and extract a feature matrix as an input to the support vector machine (SVM) classifier. A successive eye-blink switch was sequentially combined with the EEG decoder in operating the lower-limb exoskeleton. Ten subjects demonstrated more than 80% accuracy in both offline (training) and online. All subjects successfully completed a gait task by wearing the lower-limb exoskeleton through the developed real-time BCI controller. The BCI controller achieved a time ratio of 1.45 compared with a manual smartwatch controller. The developed system can potentially be benefit people with neurological disorders who may have difficulties operating manual control.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.