ArticleJournal of neural engineering2013
Quadcopter control in three-dimensional space using a noninvasive motor imagery-based brain-computer interface.
Article in Journal of neural engineering, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 122 papers, 2 of them syntheses that pooled it.
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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.
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Who cites it
122 citing papers in PubMed, 2 syntheses or guidelines pooled it, 583 citations in OpenAlex.
- EEG-Based BCIs on Motor Imagery Paradigm Using Wearable Technologies: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- Beyond Technologies of Electroencephalography-Based Brain-Computer Interfaces: A Systematic Review From Commercial and Ethical Aspects.Frontiers in neuroscience · 2020Pooled it
- Virtual and Actual Humanoid Robot Control with Four-Class Motor-Imagery-Based Optical Brain-Computer Interface.BioMed research international · 2017Trial
- Sensory-guided human-machine joint learning accelerates the acquisition of motor imagery brain computer interface control.Nature communications · 2026Article
- A Deep Learning Framework for EEG-Based Decoding of Visually Imagined Arrows with Different Colors and Directions.Biosensors · 2026Article
- Adaptive Neural Reorganization Enables Real-Time Finger-Level Robotic Control in BCI-Naïve Stroke Survivors.bioRxiv : the preprint server for biology · 2026Article
- Individualized brain-computer interface for people with disabilities: a review.Frontiers in human neuroscience · 2026Review
- Temporal convolutional transformer for EEG based motor imagery decoding.Scientific reports · 2025Article
- [Prospects and technical challenges of non-invasive brain-computer interfaces in manned space missions].Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025Article
- Investigating the neurovascular coupling across multiple motor execution and imagery conditions: a whole-brain EEG-informed fMRI analysis.NeuroImage · 2025Article
- EEG-based brain-computer interface enables real-time robotic hand control at individual finger level.Nature communications · 2025Article
- Adaptive GCN and Bi-GRU-Based Dual Branch for Motor Imagery EEG Decoding.Sensors (Basel, Switzerland) · 2025Article
- Exploring individual biases in BCI research and users: Does gender matter?Frontiers in human neuroscience · 2025Article
- Continuous Reaching and Grasping With a BCI Controlled Robotic Arm in Healthy and Stroke-Affected Individuals.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2025Article
- A high-performance brain-computer interface for finger decoding and quadcopter game control in an individual with paralysis.Nature medicine · 2025Article
- Non-Invasive Brain-Computer Interfaces: State of the Art and Trends.IEEE reviews in biomedical engineering · 2025Review
- A Bibliometric Review of Brain-Computer Interfaces in Motor Imagery and Steady-State Visually Evoked Potentials for Applications in Rehabilitation and Robotics.Sensors (Basel, Switzerland) · 2024Review
- A continuous pursuit dataset for online deep learning-based EEG brain-computer interface.Scientific data · 2024Article
- Improving inter-session performance via relevant session-transfer for multi-session motor imagery classification.Heliyon · 2024Article
- Intelligent Control System for Brain-Controlled Mobile Robot Using Self-Learning Neuro-Fuzzy Approach.Sensors (Basel, Switzerland) · 2024Article
62 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
objectiveAt the balanced intersection of human and machine adaptation is found the optimally functioning brain-computer interface (BCI). In this study, we report a novel experiment of BCI controlling a robotic quadcopter in three-dimensional (3D) physical space using noninvasive scalp electroencephalogram (EEG) in human subjects. We then quantify the performance of this system using metrics suitable for asynchronous BCI. Lastly, we examine the impact that the operation of a real world device has on subjects' control in comparison to a 2D virtual cursor task. APPROACH: Five human subjects were trained to modulate their sensorimotor rhythms to control an AR Drone navigating a 3D physical space. Visual feedback was provided via a forward facing camera on the hull of the drone. MAIN
resultsIndividual subjects were able to accurately acquire up to 90.5% of all valid targets presented while travelling at an average straight-line speed of 0.69 m s(-1). SIGNIFICANCE: Freely exploring and interacting with the world around us is a crucial element of autonomy that is lost in the context of neurodegenerative disease. Brain-computer interfaces are systems that aim to restore or enhance a user's ability to interact with the environment via a computer and through the use of only thought. We demonstrate for the first time the ability to control a flying robot in 3D physical space using noninvasive scalp recorded EEG in humans. Our work indicates the potential of noninvasive EEG-based BCI systems for accomplish complex control in 3D physical space. The present study may serve as a framework for the investigation of multidimensional noninvasive BCI control in a physical environment using telepresence robotics.
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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.