SynthesisFrontiers in human neuroscience2022
EEG-based Brain-Computer Interfaces for people with Disorders of Consciousness: Features and applications. A systematic review.
Synthesis in Frontiers in human neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.
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Who cites it
20 citing papers in PubMed, 2 syntheses or guidelines pooled it, 29 citations in OpenAlex.
- Research hotspots and trends in the application of electroencephalography for assessment of disorders of consciousness: a bibliometric analysis.Frontiers in neurology · 2024Pooled it
- Research progress on occupational therapy for disorders of consciousness in the context of neurorehabilitation: visual analysis based on CiteSpace.Frontiers in neurologyPooled it
- Brain-computer interface: an update for the clinicians.Frontiers in human neuroscience · 2026Review
- Multimodal biomarkers of response to transcutaneous auricular vagus nerve stimulation in disorders of consciousness: a study protocol.Frontiers in human neuroscience · 2026Article
- Beyond the brain: a computational MRI-derived neurophysiological framework for robotic conscious capacity.Neuroscience and biobehavioral reviews · 2025Review
- Sensitive and specific fNIRS-based approach for awareness detection in disorders of consciousness: proof of principle in healthy adults.Neurophotonics · 2025Article
- A review of hybrid EEG-based multimodal human-computer interfaces using deep learning: applications, advances, and challenges.Biomedical engineering letters · 2025Review
- [Brain-computer interface technology and its applications for patients with disorders of consciousness].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025Review
- [Detection of motor intention in patients with consciousness disorder based on electroencephalogram and functional near infrared spectroscopy combined with motor brain-computer interface paradigm].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025Article
- Parallel EEG-fNIRS assessments of covert cognition in behaviorally non-responsive ICU patients: A multi-task feasibility study in a case of acute motor sensory axonal neuropathy.Journal of neurology · 2025Article
- Disorders of Consciousness, Language and Communication Following Severe Brain Injury.Psychologica Belgica · 2025Review
- Motor imagery-based brain-computer interface for differential diagnosis in prolonged disorders of consciousness.Frontiers in human neuroscience · 2025Article
- Classification of finger movements through optimal EEG channel and feature selection.Frontiers in human neuroscience · 2025Article
- Brain-Computer Interfaces for Communication in Patients with Disorders of Consciousness: A Gap Analysis and Scientific Roadmap.Neurocritical care · 2024Review
- Review
- Brain-computer interfaces and human factors: the role of language and cultural differences-Still a missing gap?Frontiers in human neuroscience · 2024Article
- EEG-based finger movement classification with intrinsic time-scale decomposition.Frontiers in human neuroscience · 2024Article
- International survey on the implementation of the European and American guidelines on disorders of consciousness.Journal of neurology · 2024Article
- Altered brain functional connectivity in vegetative state and minimally conscious state.Frontiers in aging neuroscience · 2023Article
- Resting-state EEG microstates as electrophysiological biomarkers in post-stroke disorder of consciousness.Frontiers in neuroscience · 2023Article
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Disorders of Consciousness (DoC) are clinical conditions following a severe acquired brain injury (ABI) characterized by absent or reduced awareness, known as coma, Vegetative State (VS)/Unresponsive Wakefulness Syndrome (VS/UWS), and Minimally Conscious State (MCS). Misdiagnosis rate between VS/UWS and MCS is attested around 40% due to the clinical and behavioral fluctuations of the patients during bedside consciousness assessments. Given the large body of evidence that some patients with DoC possess "covert" awareness, revealed by neuroimaging and neurophysiological techniques, they are candidates for intervention with brain-computer interfaces (BCIs). Objectives: The aims of the present work are (i) to describe the characteristics of BCI systems based on electroencephalography (EEG) performed on DoC patients, in terms of control signals adopted to control the system, characteristics of the paradigm implemented, classification algorithms and applications (ii) to evaluate the performance of DoC patients with BCI. Methods: The search was conducted on Pubmed, Web of Science, Scopus and Google Scholar. The PRISMA guidelines were followed in order to collect papers published in english, testing a BCI and including at least one DoC patient. Results: Among the 527 papers identified with the first run of the search, 27 papers were included in the systematic review. Characteristics of the sample of participants, behavioral assessment, control signals employed to control the BCI, the classification algorithms, the characteristics of the paradigm, the applications and performance of BCI were the data extracted from the study. Control signals employed to operate the BCI were: P300 ( Conclusion: Despite the BCI is a promising tool in the management of DoC patients, supporting diagnosis and prognosis evaluation, results are still preliminary, and no definitive conclusions may be drawn; even though neurophysiological methods, such as BCI, are more sensitive to covert cognition, it is suggested to adopt a multimodal approach and a repeated assessment strategy.
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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.