SynthesisSensors (Basel, Switzerland)2018
EEG-Based Control for Upper and Lower Limb Exoskeletons and Prostheses: A Systematic Review.
Synthesis in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis 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
30 citing papers in PubMed, 1 synthesis or guideline pooled it, 144 citations in OpenAlex.
- A Systematic Review Establishing the Current State-of-the-Art, the Limitations, and the DESIRED Checklist in Studies of Direct Neural Interfacing With Robotic Gait Devices in Stroke Rehabilitation.Frontiers in neuroscience · 2020Pooled it
- Technical system of electroencephalography-based brain-computer interface: Advances, applications, and challenges.Neural regeneration research · 2026Article
- Recent Advances in Sensor-Based Upper-Limb and Hand Exoskeletons for Post-Stroke Rehabilitation: A Technical and Biomedical Review.Sensors (Basel, Switzerland) · 2026Review
- The classification of walking and phases of gait using EEG: a scoping review.Journal of neuroengineering and rehabilitation · 2026Article
- 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
- Movement speed of an autonomous prosthetic limb shapes embodiment, usability and robotic social attributes in virtual reality.Scientific reports · 2026Article
- Enhancing User Experience in Virtual Reality Through Optical Flow Simplification with the Help of Physiological Measurements: Pilot Study.Sensors (Basel, Switzerland) · 2026Article
- Dynamic graph based attention spectral network for motor imagery-brain computer interface.Frontiers in human neuroscience · 2026Article
- Lower-Limb Motor Imagery Recognition Prototype Based on EEG Acquisition, Filtering, and Machine Learning-Based Pattern Detection.Sensors (Basel, Switzerland) · 2025Article
- Temporal convolutional transformer for EEG based motor imagery decoding.Scientific reports · 2025Article
- Master classes of the tenth international brain-computer interface meeting: showcasing the research of BCI trainees.Journal of neural engineering · 2025Article
- Hybrid Functional Near-Infrared Spectroscopy System and Electromyography for Prosthetic Knee Control.Biosensors · 2024Article
- Biosignal-integrated robotic systems with emerging trends in visual interfaces: A systematic review.Biophysics reviews · 2024Review
- Merging Humans and Neuroprosthetics through Regenerative Peripheral Nerve Interfaces.Seminars in plastic surgery · 2024Review
- Exploring Convolutional Neural Network Architectures for EEG Feature Extraction.Sensors (Basel, Switzerland) · 2024Article
- Recent progress on smart lower prosthetic limbs: a comprehensive review on using EEG and fNIRS devices in rehabilitation.Frontiers in bioengineering and biotechnology · 2024Review
- Investigating the impact of visual perspective in a motor imagery-based brain-robot interaction: A pilot study with healthy participants.Frontiers in neuroergonomics · 2023Article
- Decoding reach-to-grasp from EEG using classifiers trained with data from the contralateral limb.Frontiers in human neuroscience · 2023Article
- A Review of Brain Activity and EEG-Based Brain-Computer Interfaces for Rehabilitation Application.Bioengineering (Basel, Switzerland) · 2022Review
- Identification of Lower-Limb Motor Tasks via Brain-Computer Interfaces: A Topical Overview.Sensors (Basel, Switzerland) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Electroencephalography (EEG) signals have great impact on the development of assistive rehabilitation devices. These signals are used as a popular tool to investigate the functions and the behavior of the human motion in recent research. The study of EEG-based control of assistive devices is still in early stages. Although the EEG-based control of assistive devices has attracted a considerable level of attention over the last few years, few studies have been carried out to systematically review these studies, as a means of offering researchers and experts a comprehensive summary of the present, state-of-the-art EEG-based control techniques used for assistive technology. Therefore, this research has three main goals. The first aim is to systematically gather, summarize, evaluate and synthesize information regarding the accuracy and the value of previous research published in the literature between 2011 and 2018. The second goal is to extensively report on the holistic, experimental outcomes of this domain in relation to current research. It is systematically performed to provide a wealthy image and grounded evidence of the current state of research covering EEG-based control for assistive rehabilitation devices to all the experts and scientists. The third goal is to recognize the gap of knowledge that demands further investigation and to recommend directions for future research in this area.
Indexed as
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.