ReviewSensors (Basel, Switzerland)2022
A Comprehensive Review of Endogenous EEG-Based BCIs for Dynamic Device Control.
Review in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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
12 citing papers in PubMed.
- Electroencephalography-Based Brain-Computer Interface System Using Tongue Movement Imagery for Wheelchair Control.Sensors (Basel, Switzerland) · 2026Article
- Prevalence and characteristics of community-dwelling older adults using mobility devices: a cross-national comparison between the United States and China.American journal of epidemiology · 2025Article
- Graph convolution network-based eeg signal analysis: a review.Medical & biological engineering & computing · 2025Review
- Development and evaluation of a non-invasive brain-spine interface using transcutaneous spinal cord stimulation.Journal of neuroengineering and rehabilitation · 2025Article
- Intention Reasoning for User Action Sequences via Fusion of Object Task and Object Action Affordances Based on Dempster-Shafer Theory.Sensors (Basel, Switzerland) · 2025Article
- Incidence and dynamics of mobility device use among community-dwelling older adults in the United States.Journal of elder policy · 2024Article
- Article
- Digital Technology Enablers of Tele-Neurorehabilitation in Pre- and Post-COVID-19 Pandemic Era - A Scoping Review.International journal of telerehabilitation · 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
- Paving the Way for Motor Imagery-Based Tele-Rehabilitation through a Fully Wearable BCI System.Sensors (Basel, Switzerland) · 2023Article
- Object Affordance-Based Implicit Interaction for Wheelchair-Mounted Robotic Arm Using a Laser Pointer.Sensors (Basel, Switzerland) · 2023Article
- Brain-Computer Interface Based on Steady-State Visual Evoked Potential Using Quick-Response Code Pattern for Wheelchair Control.Sensors (Basel, Switzerland) · 2023Article
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.
Funding
Abstract
Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) provide a novel approach for controlling external devices. BCI technologies can be important enabling technologies for people with severe mobility impairment. Endogenous paradigms, which depend on user-generated commands and do not need external stimuli, can provide intuitive control of external devices. This paper discusses BCIs to control various physical devices such as exoskeletons, wheelchairs, mobile robots, and robotic arms. These technologies must be able to navigate complex environments or execute fine motor movements. Brain control of these devices presents an intricate research problem that merges signal processing and classification techniques with control theory. In particular, obtaining strong classification performance for endogenous BCIs is challenging, and EEG decoder output signals can be unstable. These issues present myriad research questions that are discussed in this review paper. This review covers papers published until the end of 2021 that presented BCI-controlled dynamic devices. It discusses the devices controlled, EEG paradigms, shared control, stabilization of the EEG signal, traditional machine learning and deep learning techniques, and user experience. The paper concludes with a discussion of open questions and avenues for future work.
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.