ArticleScientific reports2016
Noninvasive Electroencephalogram Based Control of a Robotic Arm for Reach and Grasp Tasks.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 120 papers, 2 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
120 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Past, Present, and Future of EEG-Based BCI Applications.Sensors (Basel, Switzerland) · 2022Pooled it
- EEG-Based Control for Upper and Lower Limb Exoskeletons and Prostheses: A Systematic Review.Sensors (Basel, Switzerland) · 2018Pooled it
- The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users.PLoS biology · 2018Trial
- Sensory-guided human-machine joint learning accelerates the acquisition of motor imagery brain computer interface control.Nature communications · 2026Article
- Single-channel gamma burst dynamics and adaptive deep learning for robust EEG motor state decoding.Biomedical engineering letters · 2026Article
- Adaptive Neural Reorganization Enables Real-Time Finger-Level Robotic Control in BCI-Naïve Stroke Survivors.bioRxiv : the preprint server for biology · 2026Article
- Dual-Manifold Contrastive Learning for Robust and Real-Time EEG Motor Decoding.Sensors (Basel, Switzerland) · 2026Article
- Brain-computer interface: an update for the clinicians.Frontiers in human neuroscience · 2026Review
- EEG-based AI-BCI wheelchair advancement: Transformer-based learning with motor imagery for brain computer interface.Biology methods & protocols · 2026Article
- Predictive fatigue-aware human-robot collaboration: a real-time, open-source ROS 2 instantiation of a three-module human-centric digital twin framework on a standard cobot.Frontiers in robotics and AI · 2026Article
- A large electroencephalogram database of freewill reaching and grasping tasks for brain machine interfaces.Scientific data · 2025Article
- Toward Natural Limb Function: A New Era in Prosthetic Innovation.Annals of neurology · 2025Review
- Brain-computer interface control with artificial intelligence copilots.Nature machine intelligence · 2025Article
- Investigating the neurovascular coupling across multiple motor execution and imagery conditions: a whole-brain EEG-informed fMRI analysis.NeuroImage · 2025Article
- Assistive Technologies for Individuals with a Disability from a Neurological Condition: A Narrative Review on the Multimodal Integration.Healthcare (Basel, Switzerland) · 2025Review
- EEG-based brain-computer interface enables real-time robotic hand control at individual finger level.Nature communications · 2025Article
- Test-retest reliability of kinematic and EEG low-beta spectral features in a robot-based arm movement task.Biomedical physics & engineering express · 2025Article
- Exploring the feasibility of olfactory brain-computer interfaces.Scientific reports · 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
- Non-Invasive Brain-Computer Interfaces: State of the Art and Trends.IEEE reviews in biomedical engineering · 2025Review
60 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
Abstract
Brain-computer interface (BCI) technologies aim to provide a bridge between the human brain and external devices. Prior research using non-invasive BCI to control virtual objects, such as computer cursors and virtual helicopters, and real-world objects, such as wheelchairs and quadcopters, has demonstrated the promise of BCI technologies. However, controlling a robotic arm to complete reach-and-grasp tasks efficiently using non-invasive BCI has yet to be shown. In this study, we found that a group of 13 human subjects could willingly modulate brain activity to control a robotic arm with high accuracy for performing tasks requiring multiple degrees of freedom by combination of two sequential low dimensional controls. Subjects were able to effectively control reaching of the robotic arm through modulation of their brain rhythms within the span of only a few training sessions and maintained the ability to control the robotic arm over multiple months. Our results demonstrate the viability of human operation of prosthetic limbs using non-invasive BCI technology.
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.