SynthesisSensors (Basel, Switzerland)2021
Brain-Computer Interfaces Systems for Upper and Lower Limb Rehabilitation: A Systematic Review.
Synthesis in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
21 citing papers in PubMed, 3 syntheses or guidelines pooled it, 71 citations in OpenAlex.
- Efficacy and safety of brain-computer interface for stroke rehabilitation: an overview of systematic review.Frontiers in human neuroscience · 2025Pooled it
- Knowledge mapping and research trends of brain-computer interface technology in rehabilitation: a bibliometric analysis.Frontiers in human neuroscience · 2024Pooled it
- Effect of different modalities of artificial intelligence rehabilitation techniques on patients with upper limb dysfunction after stroke-A network meta-analysis of randomized controlled trials.Frontiers in neurology · 2023Pooled it
- Neurofeedback-Guided Motor Imagery in Chronic Stroke: A Case Series on Upper-Limb Recovery, Cortical Activation, and Brain Symmetry.Applied psychophysiology and biofeedback · 2026Article
- The Effectiveness of Cognitive Training Using Electroencephalography in Acute Stroke Cases.Journal of clinical medicine · 2026Article
- Decoding lower-limb movement attempts from electro-encephalographic signals in spinal cord injury patients.APL bioengineering · 2026Article
- Modern Technologies Supporting Motor Rehabilitation After Stroke: A Narrative Review.Journal of clinical medicine · 2025Review
- Recommendations for Combining Brain-Computer Interface, Motor Imagery, and Virtual Reality in Upper Limb Stroke Rehabilitation: Qualitative Participatory Design Study.JMIR rehabilitation and assistive technologies · 2025Article
- Brain-Computer Interfaces in Rehabilitation: Implementation Models and Future Perspectives.Cureus · 2025Article
- Sensorimotor correlates of sit-to-stand in healthy adults.Frontiers in bioengineering and biotechnology · 2025Article
- Neurophysiological insights into sit-to-stand post stroke.Frontiers in neuroscience · 2025Article
- Emerging Wearable Ultrasound Technology.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2024Review
- Developing a tablet-based brain-computer interface and robotic prototype for upper limb rehabilitation.PeerJ. Computer science · 2024Article
- Virtual reality a technological miracle transforming physical rehabilitation: A scoping review.Journal of family medicine and primary care · 2023Article
- Source-Based EEG Neurofeedback for Sustained Motor Imagery of a Single Leg.Sensors (Basel, Switzerland) · 2023Article
- Community mobility and participation assessment of manual wheelchair users: a review of current techniques and challenges.Frontiers in human neuroscience · 2023Review
- Identifying Thematics in a Brain-Computer Interface Research.Computational intelligence and neuroscience · 2023Review
- A Review of Brain Activity and EEG-Based Brain-Computer Interfaces for Rehabilitation Application.Bioengineering (Basel, Switzerland) · 2022Review
- Update on Stroke Rehabilitation in Motor Impairment.Brain & NeuroRehabilitation · 2022Review
- Integration of Inertial Sensors in a Lower Limb Robotic Exoskeleton.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, various studies have demonstrated the potential of electroencephalographic (EEG) signals for the development of brain-computer interfaces (BCIs) in the rehabilitation of human limbs. This article is a systematic review of the state of the art and opportunities in the development of BCIs for the rehabilitation of upper and lower limbs of the human body. The systematic review was conducted in databases considering using EEG signals, interface proposals to rehabilitate upper/lower limbs using motor intention or movement assistance and utilizing virtual environments in feedback. Studies that did not specify which processing system was used were excluded. Analyses of the design processing or reviews were excluded as well. It was identified that 11 corresponded to applications to rehabilitate upper limbs, six to lower limbs, and one to both. Likewise, six combined visual/auditory feedback, two haptic/visual, and two visual/auditory/haptic. In addition, four had fully immersive virtual reality (VR), three semi-immersive VR, and 11 non-immersive VR. In summary, the studies have demonstrated that using EEG signals, and user feedback offer benefits including cost, effectiveness, better training, user motivation and there is a need to continue developing interfaces that are accessible to users, and that integrate feedback techniques.
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Identifiers
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.